Status
±
Terminal Output
| Builder file created | |
| Configuration file | |
| ProBound run | |
| Sequence logos |
Terminal output
Pipeline Output:
> Converts the configuration file to work on run server, checks input OK > Builds configuration file OK > Runs ProBound OK > Runs Model Viewer OK
Configuration Builder File
±
ProBound builder configuration file:
[{"function": "optimizerSetting", "likelihoodThreshold": 0.0002, "pseudocount": 20, "lambdaL2": 1e-06}, {"function": "addTable", "leftFlank": "ACACTCTTTCCCTACACGACGCTCTTCCGATCTTGACGTC", "nColumns": 2, "modeledColumns": [0, 1], "countTableFile": "jobs/f2900d99a9ca/countTable.0.tsv.gz", "rightFlank": "GACGTCAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG", "inputFileType": "tsv.gz", "variableRegionLength": 30}, {"function": "addSELEX"}, {"function": "addNS"}, {"function": "addBindingMode", "flankLength": 5, "size": 12}, {"function": "addBindingMode", "flankLength": 5, "size": 12}, {"function": "bindingModeConstraints", "index": 1, "maxFlankLength": -1, "maxSize": 18, "fittingStages": [{"optimizeFlankLength": true}, {"optimizeMotifShiftHeuristic": true}, {"optimizeSizeHeuristic": true}]}, {"function": "bindingModeConstraints", "index": 2, "maxFlankLength": -1, "maxSize": 18, "fittingStages": [{"optimizeFlankLength": true}, {"optimizeMotifShiftHeuristic": true}, {"optimizeSizeHeuristic": true}]}, {"function": "output", "outputPath": "jobs/f2900d99a9ca", "baseName": "fit", "storeHessian": false, "printTrajectory": false}]Configuration File
±
ProBound configuration file:
{
"optimizerSetting": {
"likelihoodThreshold": 2.0E-4,
"nThreads": 4,
"lambdaL2": 1.0E-6,
"pseudocount": 20,
"patternSearchSettings": {},
"minimizerType": "lbfgs",
"nRetries": 3,
"hkSettings": {},
"output": {
"storeHessian": false,
"outputPath": "jobs/f2900d99a9ca",
"printTrajectory": false,
"baseName": "fit",
"printPSAM": false,
"verbose": true
},
"lbfgsSettings": {},
"sgdSettings": {},
"fixedLibrarySize": false,
"expBound": 40,
"slbfgs_plsSettings": {},
"slbfgsSettings": {}
},
"modelSettings": {
"enrichmentModel": [{
"r0KUsed": 1,
"round": 1,
"bindingSaturation": false,
"concentration": 1,
"modelType": "SELEX",
"bindingModeInteractions": [-1],
"r0KsTested": [1],
"bindingModes": [-1],
"modifications": []
}],
"countTable": [{
"leftFlank": "ACACTCTTTCCCTACACGACGCTCTTCCGATCTTGACGTC",
"transliterate": {
"in": [],
"out": []
},
"variableRegionLength": 30,
"modeledColumns": [
0,
1
],
"inputFileType": "tsv.gz",
"nColumns": 2,
"rightFlank": "GACGTCAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG",
"countTableFile": "jobs/f2900d99a9ca/countTable.0.tsv.gz"
}],
"bindingModeInteractions": [],
"bindingModes": [
{
"size": 0,
"fitLogActivity": true,
"flankLength": 0,
"dinucleotideDistance": 0,
"positionBias": false,
"singleStrand": false,
"modifications": []
},
{
"size": 12,
"fitLogActivity": true,
"flankLength": 5,
"dinucleotideDistance": 0,
"positionBias": false,
"singleStrand": false,
"modifications": []
},
{
"size": 12,
"fitLogActivity": true,
"flankLength": 5,
"dinucleotideDistance": 0,
"positionBias": false,
"singleStrand": false,
"modifications": []
}
],
"letterComplement": "C-G,A-T"
},
"modelFittingConstraints": {
"enrichmentModel": [{
"fitDelta": [false],
"roundSpecificGamma": true,
"fitRho": false,
"roundSpecificDelta": true,
"fitGamma": false,
"trySaturation": false,
"roundSpecificRho": true
}],
"nShifts": 0,
"countTable": [{}],
"addBindingModesSequentially": true,
"flankLengths": [0],
"bindingModeInteractions": [],
"singleModeLengthSweep": false,
"bindingModes": [
{
"maxFlankLength": -1,
"positionBiasBinWidth": 1,
"optimizeSizeHeuristic": false,
"maxSize": -1,
"optimizeFlankLength": false,
"symmetryString": "null",
"roundSpecificActivity": true,
"informationThreshold": 0.1,
"optimizeMotifShift": false,
"fittingStages": [],
"optimizeMotifShiftHeuristic": false,
"experimentSpecificPositionBias": true,
"minSize": -1,
"experimentSpecificActivity": true,
"optimizeSize": false
},
{
"maxFlankLength": -1,
"positionBiasBinWidth": 1,
"maxSize": 18,
"optimizeSizeHeuristic": false,
"optimizeFlankLength": false,
"symmetryString": "null",
"roundSpecificActivity": true,
"informationThreshold": 0.1,
"optimizeMotifShift": false,
"fittingStages": [
{"optimizeFlankLength": true},
{"optimizeMotifShiftHeuristic": true},
{"optimizeSizeHeuristic": true}
],
"optimizeMotifShiftHeuristic": false,
"experimentSpecificPositionBias": true,
"minSize": -1,
"experimentSpecificActivity": true,
"optimizeSize": false
},
{
"maxFlankLength": -1,
"positionBiasBinWidth": 1,
"maxSize": 18,
"optimizeSizeHeuristic": false,
"optimizeFlankLength": false,
"symmetryString": "null",
"roundSpecificActivity": true,
"informationThreshold": 0.1,
"optimizeMotifShift": false,
"fittingStages": [
{"optimizeFlankLength": true},
{"optimizeMotifShiftHeuristic": true},
{"optimizeSizeHeuristic": true}
],
"optimizeMotifShiftHeuristic": false,
"experimentSpecificPositionBias": true,
"minSize": -1,
"experimentSpecificActivity": true,
"optimizeSize": false
}
]
}
}Probound Text Output
±
Output from ProBound:
> Reading configuration JSON object and validating general schema.
> Validating configuration schema.
{"enrichmentModel":[{"fitDelta":[false],"roundSpecificGamma":true,"fitRho":false,"roundSpecificDelta":true,"fitGamma":false,"trySaturation":false,"roundSpecificRho":true}],"nShifts":0,"countTable":[{}],"addBindingModesSequentially":true,"flankLengths":[0],"bindingModeInteractions":[],"singleModeLengthSweep":false,"bindingModes":[{"maxFlankLength":-1,"positionBiasBinWidth":1,"optimizeSizeHeuristic":false,"maxSize":-1,"optimizeFlankLength":false,"symmetryString":"null","roundSpecificActivity":true,"informationThreshold":0.1,"optimizeMotifShift":false,"fittingStages":[],"optimizeMotifShiftHeuristic":false,"experimentSpecificPositionBias":true,"minSize":-1,"experimentSpecificActivity":true,"optimizeSize":false},{"maxFlankLength":-1,"positionBiasBinWidth":1,"maxSize":18,"optimizeSizeHeuristic":false,"optimizeFlankLength":false,"symmetryString":"null","roundSpecificActivity":true,"informationThreshold":0.1,"optimizeMotifShift":false,"fittingStages":[{"optimizeFlankLength":true},{"optimizeMotifShiftHeuristic":true},{"optimizeSizeHeuristic":true}],"optimizeMotifShiftHeuristic":false,"experimentSpecificPositionBias":true,"minSize":-1,"experimentSpecificActivity":true,"optimizeSize":false},{"maxFlankLength":-1,"positionBiasBinWidth":1,"maxSize":18,"optimizeSizeHeuristic":false,"optimizeFlankLength":false,"symmetryString":"null","roundSpecificActivity":true,"informationThreshold":0.1,"optimizeMotifShift":false,"fittingStages":[{"optimizeFlankLength":true},{"optimizeMotifShiftHeuristic":true},{"optimizeSizeHeuristic":true}],"optimizeMotifShiftHeuristic":false,"experimentSpecificPositionBias":true,"minSize":-1,"experimentSpecificActivity":true,"optimizeSize":false}]}
Entry=bindingModes, aEntry=[{"maxFlankLength":-1,"positionBiasBinWidth":1,"optimizeSizeHeuristic":false,"maxSize":-1,"optimizeFlankLength":false,"symmetryString":"null","roundSpecificActivity":true,"informationThreshold":0.1,"optimizeMotifShift":false,"fittingStages":[],"optimizeMotifShiftHeuristic":false,"experimentSpecificPositionBias":true,"minSize":-1,"experimentSpecificActivity":true,"optimizeSize":false},{"maxFlankLength":-1,"positionBiasBinWidth":1,"maxSize":18,"optimizeSizeHeuristic":false,"optimizeFlankLength":false,"symmetryString":"null","roundSpecificActivity":true,"informationThreshold":0.1,"optimizeMotifShift":false,"fittingStages":[{"optimizeFlankLength":true},{"optimizeMotifShiftHeuristic":true},{"optimizeSizeHeuristic":true}],"optimizeMotifShiftHeuristic":false,"experimentSpecificPositionBias":true,"minSize":-1,"experimentSpecificActivity":true,"optimizeSize":false},{"maxFlankLength":-1,"positionBiasBinWidth":1,"maxSize":18,"optimizeSizeHeuristic":false,"optimizeFlankLength":false,"symmetryString":"null","roundSpecificActivity":true,"informationThreshold":0.1,"optimizeMotifShift":false,"fittingStages":[{"optimizeFlankLength":true},{"optimizeMotifShiftHeuristic":true},{"optimizeSizeHeuristic":true}],"optimizeMotifShiftHeuristic":false,"experimentSpecificPositionBias":true,"minSize":-1,"experimentSpecificActivity":true,"optimizeSize":false}]
Entry=bindingModeInteractions, aEntry=[]
Entry=countTable, aEntry=[{}]
Entry=enrichmentModel, aEntry=[{"fitDelta":[false],"roundSpecificGamma":true,"fitRho":false,"roundSpecificDelta":true,"fitGamma":false,"trySaturation":false,"roundSpecificRho":true}]
> Builds likelihood object.
>> Creating CombinedLikelihood object.
Alphabet
========
Letter Complement: C-G,A-T
Letter Order: ACGT
Optimizer settings:
===================
lambdaL2 = 1.0E-6
pseudocount = 20.0
expBound = 40.0
fixedLibrarySize = false
>> Determining fitting order.
Summary of experiments
======================
Experiment 0:
-------------
Count table: Count table 0
Enrichment model: SELEX enrichment model 0
Concentration: 1.0
Binding modes:
Binding mode 0
Binding mode 1
Binding mode 2
Binding mode interactions:
NONE
> Builds optimizer.
> Using LBFGS.
> Starting optimization.
==================================
== Starts fiting Binding mode 0 ==
==================================
> Optimizing h (component0-0-h).
>> Starting new optimization: component0-0-h. (2021-05-21 12:21:04.49).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[0,1]}],"bindingModeInteractions":[],"bindingModes":[{},{},{}]}
Value and gradient before optimization:
=======================================
value = 2.9705114646731228
gradient = {0.4161,-0.4161}
gradient norm = 0.5884620922563474
Starting Function Value: 2.9705114646731228
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.689305107578006 5.000000000000000 8.496724029968420 0.099205548957612
2 5 0.679400995937297 0.198551806560456 0.275262127795973 0.000997261420563
3 6 0.679399973778579 0.002016205165895 1.000000000000000 0.000016758452283
4 7 0.679399973489811 0.002016205165895 1.000000000000000 0.000000004026553
Convergence criteria met.
After: gradient norm = 4.026552908411802E-9
>>> Parameters after optimization
Count Table 0:
---------------
h: {-3.3937,3.3937}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-7.1229,-7.1229}
Binding mode 1:
---------------
Mononucleotide: {-0.0008,0.0018,0.0018,0.0030,-0.0031,0.0046,-0.0012,0.0021,-0.0024,-0.0019,0.0012,-0.0021,-0.0007,-0.0021,0.0046,0.0050,0.0037,-0.0014,-0.0026,0.0043,-0.0049,0.0044,-0.0039,-0.0007,-0.0013,0.0033,0.0046,-0.0046,-0.0018,0.0039,0.0036,-0.0020,0.0036,-0.0049,-0.0042,-0.0030,0.0006,0.0039,0.0015,-0.0037,0.0016,0.0022,-0.0020,0.0017,-0.0037,-0.0027,-0.0022,-0.0013}
Activity(exp=0): {0.0000,0.0000}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
> Initial optimization (component0-1-f0).
>> Starting new optimization: component0-1-f0. (2021-05-21 12:21:05.764).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[2,3]}],"bindingModeInteractions":[],"bindingModes":[{"mononucleotide":[],"activity":[[0,1]]},{},{}]}
Value and gradient before optimization:
=======================================
value = 0.6793999734898213
gradient = {-0.0000,-0.0000,-0.0000,0.0000}
gradient norm = 2.5401038094821883E-5
Starting Function Value: 0.6793999734898213
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.679399971554365 0.000148266509926 5.837025611802440 0.000045396111050
2 6 0.679399909385932 0.002892143281934 21.000000000000000 0.000074062011093
3 7 0.679395612778900 0.262677479769671 1.000000000000000 0.001478204332731
4 8 0.679388613459509 0.515986720982004 1.000000000000000 0.002825877656486
5 9 0.679369670984416 1.567650648452062 1.000000000000000 0.004923594198015
6 10 0.679337677747003 2.955914533474505 1.000000000000000 0.006388435573448
7 11 0.679299678832077 3.987149151862392 1.000000000000000 0.005498399739623
8 12 0.679279604954849 2.231015327617393 1.000000000000000 0.002405326917091
9 13 0.679275733391978 0.009026549237229 1.000000000000000 0.000379566071804
10 14 0.679275509864195 0.298056126316019 1.000000000000000 0.000000228265982
11 15 0.679275506247285 0.057401629517133 1.000000000000000 0.000003281782193
12 16 0.679275506232140 0.002860866264177 1.000000000000000 0.000000159225083
13 17 0.679275506232087 0.002860866264177 1.000000000000000 0.000000001988082
Convergence criteria met.
After: gradient norm = 1.9880815326301E-9
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.1118,-0.1118}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-0.0008,0.0018,0.0018,0.0030,-0.0031,0.0046,-0.0012,0.0021,-0.0024,-0.0019,0.0012,-0.0021,-0.0007,-0.0021,0.0046,0.0050,0.0037,-0.0014,-0.0026,0.0043,-0.0049,0.0044,-0.0039,-0.0007,-0.0013,0.0033,0.0046,-0.0046,-0.0018,0.0039,0.0036,-0.0020,0.0036,-0.0049,-0.0042,-0.0030,0.0006,0.0039,0.0015,-0.0037,0.0016,0.0022,-0.0020,0.0017,-0.0037,-0.0027,-0.0022,-0.0013}
Activity(exp=0): {0.0000,0.0000}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
Suggested variations:
key=0;0;0, description = Initial model.
> Optimizing variation "Initial model." (component0-2-variation0).
>> Starting new optimization: component0-2-variation0. (2021-05-21 12:21:07.284).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[2,3]}],"bindingModeInteractions":[],"bindingModes":[{"mononucleotide":[],"activity":[[0,1]]},{},{}]}
Value and gradient before optimization:
=======================================
value = 0.679275506232087
gradient = {-0.0000,-0.0000,0.0000,-0.0000}
gradient norm = 1.9880815330271808E-9
Already at minimum!
After: gradient norm = 1.9880815330271808E-9
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.1118,-0.1118}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-0.0008,0.0018,0.0018,0.0030,-0.0031,0.0046,-0.0012,0.0021,-0.0024,-0.0019,0.0012,-0.0021,-0.0007,-0.0021,0.0046,0.0050,0.0037,-0.0014,-0.0026,0.0043,-0.0049,0.0044,-0.0039,-0.0007,-0.0013,0.0033,0.0046,-0.0046,-0.0018,0.0039,0.0036,-0.0020,0.0036,-0.0049,-0.0042,-0.0030,0.0006,0.0039,0.0015,-0.0037,0.0016,0.0022,-0.0020,0.0017,-0.0037,-0.0027,-0.0022,-0.0013}
Activity(exp=0): {0.0000,0.0000}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID NOT improve. Discarding fit component0-2-variation0.
> No varitions possible for Binding mode 0.
> Optimizing the full model (component0-4-all).
>> Starting new optimization: component0-4-all. (2021-05-21 12:21:07.309).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[2,3]}],"bindingModeInteractions":[],"bindingModes":[{"mononucleotide":[],"activity":[[0,1]]},{},{}]}
Value and gradient before optimization:
=======================================
value = 0.679275506232087
gradient = {-0.0000,-0.0000,0.0000,-0.0000}
gradient norm = 1.9880815328952525E-9
Already at minimum!
After: gradient norm = 1.9880815328952525E-9
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.1118,-0.1118}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-0.0008,0.0018,0.0018,0.0030,-0.0031,0.0046,-0.0012,0.0021,-0.0024,-0.0019,0.0012,-0.0021,-0.0007,-0.0021,0.0046,0.0050,0.0037,-0.0014,-0.0026,0.0043,-0.0049,0.0044,-0.0039,-0.0007,-0.0013,0.0033,0.0046,-0.0046,-0.0018,0.0039,0.0036,-0.0020,0.0036,-0.0049,-0.0042,-0.0030,0.0006,0.0039,0.0015,-0.0037,0.0016,0.0022,-0.0020,0.0017,-0.0037,-0.0027,-0.0022,-0.0013}
Activity(exp=0): {0.0000,0.0000}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
==================================
== Starts fiting Binding mode 1 ==
==================================
> Optimizing h (component1-0-h).
>> Starting new optimization: component1-0-h. (2021-05-21 12:21:07.658).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[0,1]}],"bindingModeInteractions":[],"bindingModes":[{},{},{}]}
Value and gradient before optimization:
=======================================
value = 0.9207385772578711
gradient = {-0.3288,0.3288}
gradient norm = 0.4650024552826403
Starting Function Value: 0.9207385772578711
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 2 0.679261411181754 1.000000000000000 2.150526279247654 0.000979905004827
2 3 0.679260425228416 0.002102880040830 1.000000000000000 0.000042272385521
3 4 0.679260423390746 0.002102880040830 1.000000000000000 0.000000010040651
Convergence criteria met.
After: gradient norm = 1.0040650676904321E-8
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.8175,-0.8175}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-0.0008,0.0018,0.0018,0.0030,-0.0031,0.0046,-0.0012,0.0021,-0.0024,-0.0019,0.0012,-0.0021,-0.0007,-0.0021,0.0046,0.0050,0.0037,-0.0014,-0.0026,0.0043,-0.0049,0.0044,-0.0039,-0.0007,-0.0013,0.0033,0.0046,-0.0046,-0.0018,0.0039,0.0036,-0.0020,0.0036,-0.0049,-0.0042,-0.0030,0.0006,0.0039,0.0015,-0.0037,0.0016,0.0022,-0.0020,0.0017,-0.0037,-0.0027,-0.0022,-0.0013}
Activity(exp=0): {-2.9295,-3.0413}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
> Initial optimization (component1-1-f0).
>> Starting new optimization: component1-1-f0. (2021-05-21 12:21:09.559).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6899951312898713
gradient = {0.0013,-0.0013,-0.0014,0.0013,0.0014,-0.0014,-0.0014,0.0014,0.0015,-0.0015,-0.0014,0.0014,0.0015,-0.0015,-0.0014,0.0015,0.0015,-0.0016,-0.0015,0.0016,0.0015,-0.0015,-0.0015,0.0015,0.0015,-0.0015,-0.0016,0.0016,0.0016,-0.0015,-0.0016,0.0015,0.0015,-0.0014,-0.0015,0.0015,0.0014,-0.0014,-0.0015,0.0015,0.0014,-0.0014,-0.0014,0.0014,0.0013,-0.0014,-0.0013,0.0013,-0.0000,-0.0000,0.0000,-0.0000}
gradient norm = 0.010058572910964625
Starting Function Value: 0.6899951312898713
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.686920767457359 0.487592274872125 48.475293581717930 0.020964445513029
2 5 0.686455595441510 0.117843684108885 0.168909704991571 0.008223728887149
3 6 0.686323814590567 0.145070474551370 1.000000000000000 0.002909269743278
4 7 0.686315615341711 0.023897048811001 1.000000000000000 0.000529926979032
5 8 0.686315003613148 0.001369211326092 1.000000000000000 0.000550655374355
6 9 0.686276244826520 0.100894877553335 1.000000000000000 0.003916845463238
7 12 0.686025040017902 0.568351966192096 1.906547370630328 0.003536256314187
8 14 0.686018292260403 0.018791338376196 0.003497064027277 0.004076975477632
9 15 0.685948481794040 0.298855164826260 1.000000000000000 0.014595704528639
10 16 0.685879669455349 0.075449913173238 1.000000000000000 0.008751105247552
11 17 0.685799217658823 0.094053386264638 1.000000000000000 0.006037643061695
12 18 0.685668846868892 0.144315148973213 1.000000000000000 0.005776000539038
13 20 0.685189776029631 0.451066253719551 0.263658517992481 0.013817507774391
14 22 0.684797810917563 0.343451386924735 0.161180175814906 0.023099683732084
15 23 0.683864070090859 0.950022312488877 1.000000000000000 0.053031735063623
16 24 0.680892629028825 0.295621097070394 1.000000000000000 0.026788964754438
17 26 0.678006007010945 0.829080780242121 0.465492894497553 0.035313069387551
18 27 0.674355316828417 0.650686968969857 1.000000000000000 0.011858022423293
19 28 0.672835936312599 0.410280306587100 1.000000000000000 0.012335794919692
20 29 0.672253480451097 0.597701303660726 1.000000000000000 0.018666224086596
21 30 0.671162471772750 0.287460781223922 1.000000000000000 0.005759646209314
22 31 0.670563526426917 0.174672111247842 1.000000000000000 0.008782667385278
23 32 0.669960195236762 0.283713701779374 1.000000000000000 0.022298842298397
24 33 0.669667565319489 0.121149038133007 1.000000000000000 0.022671780530582
25 34 0.668189921992161 0.578039923960563 1.000000000000000 0.017456439055926
26 35 0.667081168027255 0.526153022748368 1.000000000000000 0.014968375048066
27 36 0.665708804881805 1.280010979161386 1.000000000000000 0.038836899947372
28 37 0.664164542779945 0.316403664176946 1.000000000000000 0.007605728464500
29 38 0.663325248259860 0.384629836649345 1.000000000000000 0.007489837499270
30 39 0.662147598973351 0.464768464108544 1.000000000000000 0.009806617849644
31 40 0.661208637099527 0.588282331698083 1.000000000000000 0.010036912148095
32 41 0.660529396195452 0.488761548849110 1.000000000000000 0.010276021278104
33 42 0.659924322457200 0.487835794501240 1.000000000000000 0.003278616890478
34 43 0.659662624707351 0.373779427461137 1.000000000000000 0.003107159402143
35 44 0.659287116322455 0.440611252456010 1.000000000000000 0.002021435243755
36 45 0.659050554896511 0.555562546533663 1.000000000000000 0.003036867185394
37 46 0.659019356565942 0.121277943623114 1.000000000000000 0.000930798374970
38 47 0.659009664354562 0.093601395602823 1.000000000000000 0.000355824457643
39 48 0.659004350702793 0.035052063445642 1.000000000000000 0.000310927276768
40 49 0.658989028555938 0.092295543905798 1.000000000000000 0.000204588095972
41 50 0.658978807773596 0.110987629824333 1.000000000000000 0.000151373151788
42 51 0.658975237450747 0.070522604906145 1.000000000000000 0.000170865709561
43 52 0.658974046446394 0.031805726990069 1.000000000000000 0.000120038818089
44 53 0.658973049171883 0.035534629942086 1.000000000000000 0.000077389452949
45 54 0.658972491217002 0.026240325905008 1.000000000000000 0.000044339992538
46 55 0.658972153570968 0.022629036764075 1.000000000000000 0.000024968177119
47 56 0.658972009926108 0.012563667066539 1.000000000000000 0.000019994996417
48 57 0.658971907607820 0.012166876958736 1.000000000000000 0.000016893338449
49 58 0.658971828554102 0.012605168686884 1.000000000000000 0.000014457973392
50 59 0.658971713412408 0.023738333860713 1.000000000000000 0.000016746768589
51 60 0.658971566372772 0.035733676923183 1.000000000000000 0.000025936341521
52 61 0.658971294110136 0.067414220124484 1.000000000000000 0.000038804628626
53 62 0.658970734015227 0.146918902490542 1.000000000000000 0.000051974236424
54 63 0.658969732374349 0.288999540339596 1.000000000000000 0.000081200867696
55 64 0.658967948417004 0.546386916175627 1.000000000000000 0.000090373182229
56 65 0.658965309726347 0.784316618504991 1.000000000000000 0.000093565299983
57 66 0.658962109251491 0.929633476069202 1.000000000000000 0.000102049171268
58 67 0.658959885917983 0.666165865338480 1.000000000000000 0.000075372877453
59 68 0.658958874537458 0.054212435333469 1.000000000000000 0.000052938149763
60 69 0.658958325057437 0.038824456834041 1.000000000000000 0.000039253514974
61 70 0.658958091306162 0.135364575946892 1.000000000000000 0.000036568232459
62 71 0.658957977839684 0.142408874428971 1.000000000000000 0.000031100755773
63 72 0.658957930953123 0.016141237671037 1.000000000000000 0.000018932205000
64 73 0.658957908351352 0.009578062513807 1.000000000000000 0.000009697432574
65 74 0.658957897262080 0.012923346162668 1.000000000000000 0.000007250257630
66 75 0.658957887843393 0.010235649372870 1.000000000000000 0.000006365312184
67 76 0.658957879935441 0.003818024833796 1.000000000000000 0.000002881422881
68 77 0.658957876936035 0.009434419576235 1.000000000000000 0.000002597441929
69 78 0.658957876486339 0.004354142094365 1.000000000000000 0.000002505333111
70 79 0.658957876178027 0.001360767064587 1.000000000000000 0.000001276121728
71 80 0.658957876093501 0.001360767064587 1.000000000000000 0.000000411490888
Convergence criteria met.
After: gradient norm = 4.1149088839113084E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2700,-0.2700}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.3610,0.4599,-0.6656,-1.1527,-1.6263,1.3284,-1.1898,-1.2316,-0.4258,0.5970,-1.3989,-1.4916,-1.4968,0.7856,-1.8548,-0.1534,-1.4348,1.6113,-1.5460,-1.3499,-1.2523,-0.6678,-1.7389,0.9396,0.2613,-1.4486,-0.6376,-0.8944,-1.6612,-0.6240,0.4467,-0.8809,-0.6194,-0.1240,-1.7534,-0.2226,-1.8175,-0.7637,1.2352,-1.3734,-1.1681,-1.3094,0.6670,-0.9089,-1.0619,-0.3398,-1.2374,-0.0803}
Activity(exp=0): {0.0005,-2.7189}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
Suggested variations:
key=12;5;0, description = Initial model.
> Optimizing variation "Initial model." (component1-2-variation0).
>> Starting new optimization: component1-2-variation0. (2021-05-21 12:22:04.465).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6589578760935012
gradient = {0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000}
gradient norm = 4.114908883912381E-7
Already at minimum!
After: gradient norm = 4.114908883912381E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2700,-0.2700}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.3610,0.4599,-0.6656,-1.1527,-1.6263,1.3284,-1.1898,-1.2316,-0.4258,0.5970,-1.3989,-1.4916,-1.4968,0.7856,-1.8548,-0.1534,-1.4348,1.6113,-1.5460,-1.3499,-1.2523,-0.6678,-1.7389,0.9396,0.2613,-1.4486,-0.6376,-0.8944,-1.6612,-0.6240,0.4467,-0.8809,-0.6194,-0.1240,-1.7534,-0.2226,-1.8175,-0.7637,1.2352,-1.3734,-1.1681,-1.3094,0.6670,-0.9089,-1.0619,-0.3398,-1.2374,-0.0803}
Activity(exp=0): {0.0005,-2.7189}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID NOT improve. Discarding fit component1-2-variation0.
Suggested variations:
key=12;6;0, description = Increases flank length.
> Optimizing variation "Increases flank length." (component1-2-variation1).
>> Starting new optimization: component1-2-variation1. (2021-05-21 12:22:05.141).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6585400338707835
gradient = {0.0001,-0.0000,0.0002,0.0001,0.0000,0.0002,0.0000,0.0000,0.0000,0.0002,0.0001,0.0000,0.0000,0.0002,0.0000,0.0000,0.0000,0.0002,0.0000,0.0000,0.0000,0.0002,0.0000,0.0000,0.0001,0.0001,-0.0001,0.0002,-0.0001,0.0001,0.0003,0.0000,0.0002,-0.0001,0.0000,0.0001,0.0000,0.0002,0.0000,0.0000,0.0000,0.0000,0.0003,-0.0001,0.0000,-0.0000,0.0000,0.0003,0.0000,0.0003,-0.0017,0.0017}
gradient norm = 0.0025157709442101715
Starting Function Value: 0.6585400338707835
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.658533491165551 0.005072680609738 2.016352331841624 0.000666431571889
2 4 0.658532606266267 0.001400484649244 1.000000000000000 0.000661787662037
3 5 0.658513313822505 0.050609145485585 1.000000000000000 0.001087130246310
4 6 0.658500417113360 0.042119119028339 1.000000000000000 0.001308559643731
5 7 0.658491165084274 0.044507872430559 1.000000000000000 0.000488780619618
6 8 0.658488075053965 0.019277193999873 1.000000000000000 0.000420586269109
7 9 0.658484872752507 0.021773919702256 1.000000000000000 0.000777803376848
8 10 0.658480402050705 0.033291373089980 1.000000000000000 0.000991881016951
9 11 0.658476292676034 0.033112258169413 1.000000000000000 0.000589556378277
10 12 0.658474916969836 0.013312218029366 1.000000000000000 0.000139712952562
11 13 0.658474572482754 0.004529612982692 1.000000000000000 0.000229717625065
12 14 0.658474273484797 0.004549987793138 1.000000000000000 0.000353186880987
13 15 0.658473639652382 0.010336126565497 1.000000000000000 0.000469751563647
14 16 0.658472794706004 0.016463097541854 1.000000000000000 0.000405885099163
15 17 0.658472062484482 0.017504842352659 1.000000000000000 0.000152443643208
16 18 0.658471822501623 0.009615048341721 1.000000000000000 0.000093936490100
17 19 0.658471747897269 0.003081399694683 1.000000000000000 0.000148839430719
18 20 0.658471602372828 0.006470222011241 1.000000000000000 0.000193941144312
19 21 0.658471427525259 0.008561268444319 1.000000000000000 0.000154746142343
20 22 0.658471262606362 0.009617749735152 1.000000000000000 0.000052719166469
21 23 0.658471194230837 0.005432726050079 1.000000000000000 0.000061138669713
22 24 0.658471162556000 0.002422258651445 1.000000000000000 0.000092486672593
23 25 0.658471116792464 0.003604141930592 1.000000000000000 0.000098743379015
24 26 0.658471037033419 0.006561937845550 1.000000000000000 0.000051270633634
25 27 0.658470995369840 0.005849015546877 1.000000000000000 0.000025255952669
26 28 0.658470987044866 0.001419120628792 1.000000000000000 0.000038570516651
27 29 0.658470975433445 0.002061780567819 1.000000000000000 0.000039939107500
28 30 0.658470948299445 0.004459499598368 1.000000000000000 0.000022471533330
29 31 0.658470935053239 0.003808322969168 1.000000000000000 0.000007282178478
30 32 0.658470932757608 0.000861428350483 1.000000000000000 0.000009920476432
31 33 0.658470928166281 0.001563056933473 1.000000000000000 0.000011267458662
32 34 0.658470919874839 0.003125734181506 1.000000000000000 0.000009765651290
33 35 0.658470916604343 0.002553538119631 1.000000000000000 0.000005182838049
34 36 0.658470916072124 0.000343869820156 1.000000000000000 0.000005155992742
35 37 0.658470915922101 0.000242013978844 1.000000000000000 0.000003646309933
36 38 0.658470915773455 0.000172913639952 1.000000000000000 0.000001621747049
37 39 0.658470915443313 0.000547840147607 1.000000000000000 0.000004796786630
38 40 0.658470915262677 0.000413150495958 1.000000000000000 0.000005722157445
39 41 0.658470915072392 0.000390721529550 1.000000000000000 0.000003057339178
40 42 0.658470914980124 0.000252966760357 1.000000000000000 0.000000961807377
41 43 0.658470914953899 0.000076870296915 1.000000000000000 0.000001960887430
42 44 0.658470914926685 0.000095639625644 1.000000000000000 0.000002402456710
43 45 0.658470914889598 0.000111580822515 1.000000000000000 0.000001801331907
44 46 0.658470914834474 0.000111580822515 1.000000000000000 0.000000649617039
Convergence criteria met.
After: gradient norm = 6.496170388145126E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2731,-0.2731}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.3535,0.5260,-0.7631,-1.1349,-1.6359,1.3257,-1.1906,-1.2248,-0.4058,0.5990,-1.4217,-1.4971,-1.4893,0.7790,-1.8865,-0.1288,-1.4171,1.5887,-1.5256,-1.3716,-1.2425,-0.7808,-1.6919,0.9897,0.2831,-1.4565,-0.5700,-0.9821,-1.5902,-0.6544,0.4210,-0.9019,-0.6531,-0.1195,-1.7052,-0.2478,-1.7960,-0.8147,1.2481,-1.3630,-1.2047,-1.3171,0.6501,-0.8538,-1.0676,-0.3151,-1.2469,-0.0960}
Activity(exp=0): {0.0005,-2.7251}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID improve.
Suggested variations:
key=12;7;0, description = Increases flank length.
> Optimizing variation "Increases flank length." (component1-2-variation2).
>> Starting new optimization: component1-2-variation2. (2021-05-21 12:22:38.446).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6584708605425772
gradient = {0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0001,0.0001}
gradient norm = 1.4325950222722193E-4
Starting Function Value: 0.6584708605425772
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.658470840436481 0.000273175241189 1.906855998677013 0.000017471789480
2 4 0.658470839868416 0.000035837120897 1.000000000000000 0.000015204660175
3 5 0.658470838111609 0.000218615260013 1.000000000000000 0.000005675865685
4 6 0.658470837839180 0.000069086847331 1.000000000000000 0.000004388940264
5 7 0.658470836621467 0.000519455078870 1.000000000000000 0.000008347445333
6 8 0.658470836311833 0.000225075036536 1.000000000000000 0.000004361801848
7 9 0.658470836194867 0.000114341859362 1.000000000000000 0.000001647811683
8 10 0.658470836147121 0.000054178340708 1.000000000000000 0.000002596040756
9 11 0.658470836066141 0.000100530781704 1.000000000000000 0.000004339261874
10 12 0.658470835947714 0.000166981621339 1.000000000000000 0.000004916501707
11 13 0.658470835783853 0.000233584170791 1.000000000000000 0.000002675051934
12 14 0.658470835689500 0.000202538209404 1.000000000000000 0.000000933452471
13 15 0.658470835666455 0.000059864868152 1.000000000000000 0.000001578518094
14 16 0.658470835643579 0.000069600475639 1.000000000000000 0.000001711144441
15 17 0.658470835605051 0.000117997302506 1.000000000000000 0.000000863418958
16 18 0.658470835581301 0.000117997302506 1.000000000000000 0.000000507801559
Convergence criteria met.
After: gradient norm = 5.078015593555022E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2734,-0.2734}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.3535,0.5261,-0.7635,-1.1347,-1.6359,1.3259,-1.1907,-1.2248,-0.4058,0.5991,-1.4218,-1.4971,-1.4893,0.7788,-1.8865,-0.1286,-1.4171,1.5884,-1.5254,-1.3715,-1.2427,-0.7807,-1.6924,0.9901,0.2833,-1.4572,-0.5699,-0.9819,-1.5903,-0.6545,0.4212,-0.9020,-0.6534,-0.1196,-1.7052,-0.2473,-1.7957,-0.8151,1.2481,-1.3628,-1.2046,-1.3175,0.6502,-0.8537,-1.0677,-0.3149,-1.2468,-0.0962}
Activity(exp=0): {0.0005,-2.7251}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID NOT improve. Discarding fit component1-2-variation2.
Suggested variations:
key=12;6;1, description = Heuristic shift (1).
> Optimizing variation "Heuristic shift (1)." (component1-2-variation3).
>> Starting new optimization: component1-2-variation3. (2021-05-21 12:22:51.931).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.663090041068272
gradient = {0.0045,0.0051,-0.0013,0.0050,0.0015,0.0080,0.0019,0.0019,0.0005,0.0110,0.0008,0.0009,0.0028,0.0079,0.0015,0.0011,0.0008,0.0084,0.0005,0.0035,0.0006,0.0117,0.0005,0.0006,0.0012,0.0021,0.0007,0.0093,0.0068,0.0014,0.0031,0.0019,0.0014,0.0032,0.0068,0.0019,0.0032,0.0052,0.0011,0.0039,0.0005,0.0022,0.0098,0.0008,0.0018,0.0013,0.0083,0.0020,0.0000,0.0133,-0.0263,0.0263}
gradient norm = 0.0507189876691246
Starting Function Value: 0.663090041068272
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.660606941370263 0.099145117246323 1.954792905038167 0.013246354460074
2 4 0.660305616436551 0.024908579052541 1.000000000000000 0.011696501443971
3 5 0.658609467363913 0.256836282906897 1.000000000000000 0.007769050313644
4 6 0.657881877298908 0.163871806619699 1.000000000000000 0.008398983507021
5 7 0.655203649075706 0.811097881351339 1.000000000000000 0.007232999810876
6 8 0.654341603703732 0.679874947669361 1.000000000000000 0.007273323900060
7 9 0.654259110055785 0.105906064121615 1.000000000000000 0.000808147496254
8 10 0.654251253826638 0.025401691920245 1.000000000000000 0.000921061266198
9 11 0.654233624059807 0.075648643752639 1.000000000000000 0.001056559617007
10 12 0.654215771218550 0.046674137647844 1.000000000000000 0.000958917989922
11 13 0.654166659108614 0.171942246992120 1.000000000000000 0.000580514762399
12 14 0.654150869774946 0.080996205370334 1.000000000000000 0.000427632181010
13 15 0.654134701053068 0.103808147523075 1.000000000000000 0.000356336229679
14 16 0.654124213604778 0.089126807133276 1.000000000000000 0.000273363414252
15 17 0.654117865131720 0.075624646114118 1.000000000000000 0.000124806481906
16 18 0.654115808223978 0.044380745668773 1.000000000000000 0.000061585682934
17 19 0.654114972605547 0.027249916592015 1.000000000000000 0.000062798989527
18 20 0.654114244255434 0.031095187289611 1.000000000000000 0.000044132406178
19 21 0.654113888581200 0.024404507508083 1.000000000000000 0.000039019385664
20 22 0.654113795939465 0.009704486873250 1.000000000000000 0.000011079094791
21 23 0.654113773502091 0.003752600592155 1.000000000000000 0.000010134567342
22 24 0.654113738092652 0.006714574764194 1.000000000000000 0.000007693429847
23 25 0.654113720555084 0.006055214019331 1.000000000000000 0.000008964278476
24 26 0.654113715283727 0.002600269023148 1.000000000000000 0.000004525212696
25 27 0.654113710556851 0.002825876938719 1.000000000000000 0.000005286854520
26 28 0.654113704901517 0.003314818975580 1.000000000000000 0.000005838834637
27 29 0.654113690876942 0.008136397769851 1.000000000000000 0.000008322291070
28 30 0.654113666937017 0.016197315088897 1.000000000000000 0.000006777712640
29 31 0.654113633819851 0.024394131634250 1.000000000000000 0.000009664856648
30 32 0.654113564696806 0.055372829698748 1.000000000000000 0.000018398664066
31 33 0.654113462762291 0.074629559683484 1.000000000000000 0.000021942837218
32 34 0.654113160524048 0.230680859775497 1.000000000000000 0.000041282098328
33 35 0.654112721567786 0.360171848410418 1.000000000000000 0.000036593364676
34 36 0.654112580237252 0.513621377149690 1.000000000000000 0.000087799897260
35 37 0.654112149765976 0.015386786719947 1.000000000000000 0.000025172790533
36 38 0.654112072327732 0.026284894354793 1.000000000000000 0.000007133545391
37 39 0.654112051257885 0.008399059940896 1.000000000000000 0.000006003618904
38 40 0.654112036896197 0.025681048376161 1.000000000000000 0.000003755876049
39 41 0.654112028342630 0.017100496650632 1.000000000000000 0.000001851842752
40 42 0.654112027974972 0.002157927552537 1.000000000000000 0.000002725272809
41 43 0.654112027383826 0.002157927552537 1.000000000000000 0.000000507201082
Convergence criteria met.
After: gradient norm = 5.072010819902227E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2684,-0.2684}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.3749,-1.1590,0.7874,-1.1008,-1.2481,0.8134,-0.8697,-1.5416,-1.6136,1.2989,-1.1342,-1.3971,-0.3146,0.6502,-1.6578,-1.5239,-1.4559,0.8388,-1.9694,-0.2596,-1.3675,1.5489,-1.5448,-1.4826,-1.1548,-0.8351,-1.8142,0.9579,0.2038,-1.3953,-0.6332,-1.0213,-1.5521,-0.6989,0.3505,-0.9455,-0.6065,-0.2091,-1.6395,-0.3910,-1.9094,-0.7314,1.1598,-1.3651,-1.1872,-1.3385,0.5040,-0.8243}
Activity(exp=0): {-0.0000,-2.8461}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID improve.
Suggested variations:
key=12;6;2, description = Heuristic shift (1).
> Optimizing variation "Heuristic shift (1)." (component1-2-variation4).
>> Starting new optimization: component1-2-variation4. (2021-05-21 12:23:22.308).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6597675067062257
gradient = {0.0032,-0.0016,0.0030,0.0023,0.0006,0.0011,0.0041,0.0010,0.0003,0.0047,0.0009,0.0010,0.0002,0.0060,0.0003,0.0004,0.0017,0.0047,0.0001,0.0005,0.0004,0.0052,0.0001,0.0012,0.0002,0.0064,0.0002,0.0002,0.0007,0.0012,0.0003,0.0047,0.0034,0.0007,0.0017,0.0011,0.0012,0.0018,0.0029,0.0010,0.0009,0.0035,0.0004,0.0020,0.0002,0.0005,0.0058,0.0004,-0.0000,0.0069,-0.0128,0.0128}
gradient norm = 0.02609401537583218
Starting Function Value: 0.6597675067062257
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.659008101989295 0.059001582025782 2.261115477092431 0.010273131445334
2 4 0.658817720150977 0.021182820240794 1.000000000000000 0.008948366748519
3 5 0.657791350647631 0.205000633534912 1.000000000000000 0.006234434357881
4 6 0.657281240251547 0.145298730662250 1.000000000000000 0.007334927750186
5 7 0.655398764232690 0.693212980165158 1.000000000000000 0.007571617211070
6 8 0.654685875640087 0.515307125712701 1.000000000000000 0.005037892353036
7 9 0.654581760275360 0.088070823918383 1.000000000000000 0.001748440911119
8 10 0.654490715634575 0.147491503748219 1.000000000000000 0.004063586114841
9 11 0.654415276577617 0.164916781902408 1.000000000000000 0.004099898605103
10 12 0.654275102641268 0.253801674192417 1.000000000000000 0.002553685722210
11 13 0.654175169587209 0.327376007058776 1.000000000000000 0.000911730846112
12 14 0.654164312951529 0.048230068221578 1.000000000000000 0.000863352348887
13 15 0.654143414584593 0.084745105030864 1.000000000000000 0.000427096645498
14 16 0.654130327956810 0.102535129998498 1.000000000000000 0.000296479744710
15 17 0.654126252186987 0.043834097780821 1.000000000000000 0.000316687161846
16 18 0.654116120575348 0.115334360424360 1.000000000000000 0.000214673743458
17 19 0.654111955790222 0.066707858828926 1.000000000000000 0.000146595253599
18 20 0.654110536480743 0.038677210744423 1.000000000000000 0.000197415236623
19 21 0.654109354523514 0.031624757007814 1.000000000000000 0.000086148984153
20 22 0.654108758355619 0.025927714644822 1.000000000000000 0.000063741252294
21 23 0.654108553187305 0.009514989129461 1.000000000000000 0.000076151164463
22 24 0.654108119090787 0.021016873018231 1.000000000000000 0.000077868678620
23 25 0.654107788961377 0.023163173038764 1.000000000000000 0.000038745784284
24 26 0.654107701045124 0.008738129641003 1.000000000000000 0.000016146655045
25 27 0.654107669648006 0.004868127316328 1.000000000000000 0.000014800337163
26 28 0.654107648581641 0.004645159247422 1.000000000000000 0.000024205046292
27 29 0.654107635826962 0.003393493232652 1.000000000000000 0.000019354683211
28 30 0.654107626708802 0.002810248319979 1.000000000000000 0.000005634397465
29 31 0.654107622955777 0.001972755400660 1.000000000000000 0.000008686491380
30 32 0.654107621151222 0.001051479482931 1.000000000000000 0.000012229764442
31 33 0.654107617840217 0.002000584751303 1.000000000000000 0.000012521753474
32 34 0.654107608837920 0.004617740414742 1.000000000000000 0.000013397011944
33 35 0.654107582340081 0.017056058915240 1.000000000000000 0.000010367290441
34 36 0.654107550575819 0.021051195034590 1.000000000000000 0.000008417553152
35 37 0.654107508180065 0.030115640028418 1.000000000000000 0.000016544029680
36 38 0.654107453100631 0.040796075172256 1.000000000000000 0.000026965707634
37 39 0.654107366973908 0.062409826487670 1.000000000000000 0.000034578178885
38 40 0.654107166302069 0.142618310705411 1.000000000000000 0.000040171286009
39 41 0.654106696951216 0.351918750431158 1.000000000000000 0.000043143667371
40 42 0.654106271459808 0.528223029259163 1.000000000000000 0.000072993205587
41 43 0.654105967896649 0.080267091886493 1.000000000000000 0.000025792008857
42 44 0.654105814784539 0.073065188745510 1.000000000000000 0.000012429525945
43 45 0.654105805981893 0.007030289489029 1.000000000000000 0.000010084856214
44 46 0.654105801398535 0.005496123547994 1.000000000000000 0.000014403215021
45 47 0.654105798829751 0.003152308583354 1.000000000000000 0.000011066986984
46 48 0.654105794469769 0.010007838015771 1.000000000000000 0.000005837697479
47 49 0.654105793080860 0.004075456105618 1.000000000000000 0.000008261421485
48 50 0.654105791912420 0.001980362803105 1.000000000000000 0.000006913206380
49 51 0.654105790999717 0.000862876120335 1.000000000000000 0.000002847888515
50 52 0.654105790521471 0.001269463750256 1.000000000000000 0.000002523294026
51 53 0.654105790381031 0.000426049833073 1.000000000000000 0.000003055982622
52 54 0.654105790205372 0.000328803180287 1.000000000000000 0.000001739642418
53 55 0.654105790094490 0.000328803180287 1.000000000000000 0.000000811622264
Convergence criteria met.
After: gradient norm = 8.11622264429796E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2634,-0.2634}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.6261,0.5939,-1.2312,-0.5289,-1.3997,-1.5079,0.9423,-0.8275,-0.6917,1.0393,-1.1830,-1.9574,-1.4643,1.4679,-1.4200,-1.3764,-0.4010,0.4998,-1.2306,-1.6610,-1.3792,0.6536,-1.7370,-0.3302,-1.2977,1.2990,-1.5843,-1.2098,-1.0170,-1.0109,-1.6236,0.8587,0.1497,-1.4004,-0.5311,-1.0110,-1.5883,-0.7430,0.3993,-0.8608,-0.5126,-0.4465,-1.2638,-0.5699,-1.8681,-0.5738,0.9634,-1.3143}
Activity(exp=0): {-0.0000,-2.7928}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID NOT improve. Discarding fit component1-2-variation4.
informationThreshold = 0.1
>>> Information used for optimizeSizeHeuristic: I[0] = 0.6733112818185757, I[1] = 0.688141893206216, I[k-2] = 0.9351183622525368, I[k-1] = 0.4576006997870864
Suggested variations:
key=14;7;2, description = Expands: deltaLeft = 1, deltaRight = 1, deltaFlank = 1.
> Optimizing variation "Expands: deltaLeft = 1, deltaRight = 1, deltaFlank = 1." (component1-2-variation5).
>> Starting new optimization: component1-2-variation5. (2021-05-21 12:24:00.974).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[58,59]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55],"activity":[[56,57]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6559011405813735
gradient = {0.0018,-0.0044,0.0013,0.0013,0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,0.0012,-0.0010,0.0014,-0.0016,-0.0000,0.0000,0.0000,-0.0000}
gradient norm = 0.005754395560578594
Starting Function Value: 0.6559011405813735
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 2 0.652976962929387 1.000000000000000 173.78019801952090 0.021691631726392
2 4 0.652378391579816 0.196017730784915 0.250169090457070 0.009737673342160
3 5 0.652182159205576 0.024816438330097 1.000000000000000 0.007985751821140
4 6 0.651647044094530 0.298415936429760 1.000000000000000 0.002782234493820
5 7 0.651603920324597 0.066427594357002 1.000000000000000 0.001596712659964
6 8 0.651542245548566 0.121016417337376 1.000000000000000 0.002461055773678
7 9 0.651473336693956 0.116492690964724 1.000000000000000 0.003568635285899
8 10 0.651332186818025 0.221734969384423 1.000000000000000 0.004108307080233
9 11 0.651174900899187 0.254009613283543 1.000000000000000 0.002569603245663
10 12 0.651128511228571 0.132844587775822 1.000000000000000 0.000622527721545
11 13 0.651117119307156 0.044994693901066 1.000000000000000 0.001112239987260
12 14 0.651104231302666 0.052586619983776 1.000000000000000 0.001478941863608
13 15 0.651087348550998 0.073881798865946 1.000000000000000 0.001286437837468
14 16 0.651064770406853 0.134071882124748 1.000000000000000 0.000554152647308
15 17 0.651056713463657 0.088896220812616 1.000000000000000 0.000238829591935
16 18 0.651054155461333 0.034339865817833 1.000000000000000 0.000393651184628
17 19 0.651051198646164 0.036033363564764 1.000000000000000 0.000431323380437
18 20 0.651046502043114 0.058216342704329 1.000000000000000 0.000257866550252
19 21 0.651044626145812 0.034896756925756 1.000000000000000 0.000089102564724
20 22 0.651043689522713 0.026774769594928 1.000000000000000 0.000190862546862
21 23 0.651043225188889 0.014592055853596 1.000000000000000 0.000228264295876
22 24 0.651042487654682 0.023692304258413 1.000000000000000 0.000151677441802
23 25 0.651042007950322 0.022768665923828 1.000000000000000 0.000044017640969
24 26 0.651041844017766 0.011073486077162 1.000000000000000 0.000088086347453
25 27 0.651041722330046 0.007510415204050 1.000000000000000 0.000120305844147
26 28 0.651041534617641 0.010690670566915 1.000000000000000 0.000112002032935
27 29 0.651041221872368 0.021106682410424 1.000000000000000 0.000069152616164
28 30 0.651041105431285 0.011787654711401 1.000000000000000 0.000021248388979
29 31 0.651041070065745 0.005355582660581 1.000000000000000 0.000025577009010
30 32 0.651041050085165 0.003180793893450 1.000000000000000 0.000033623522074
31 33 0.651041017185981 0.004982097780133 1.000000000000000 0.000029846828599
32 34 0.651040975364039 0.008264493567647 1.000000000000000 0.000012897836739
33 35 0.651040962672409 0.003679998254771 1.000000000000000 0.000006720824775
34 36 0.651040954878553 0.002691510652902 1.000000000000000 0.000011874894152
35 37 0.651040948222885 0.003001188670842 1.000000000000000 0.000013275299292
36 38 0.651040934375159 0.005254322741351 1.000000000000000 0.000014216998408
37 39 0.651040885226010 0.023224890666269 1.000000000000000 0.000012115596441
38 40 0.651040820447082 0.029952832038397 1.000000000000000 0.000014874143244
39 41 0.651040666224261 0.076391812224175 1.000000000000000 0.000032068338616
40 42 0.651040415768396 0.135675433243836 1.000000000000000 0.000047879680929
41 43 0.651039968188674 0.240104136030241 1.000000000000000 0.000075369434729
42 44 0.651039240595176 0.439904740190316 1.000000000000000 0.000042338678964
43 45 0.651038676757062 0.355851289165345 1.000000000000000 0.000068079563790
44 46 0.651038288802155 0.201750527824970 1.000000000000000 0.000054691997617
45 47 0.651038105216974 0.030203837842830 1.000000000000000 0.000052433097743
46 48 0.651037720071145 0.159436205864181 1.000000000000000 0.000037702046761
47 49 0.651037522521768 0.147580181761787 1.000000000000000 0.000011275381806
48 50 0.651037499568695 0.020437156641391 1.000000000000000 0.000010271515630
49 51 0.651037490323034 0.006433163891539 1.000000000000000 0.000009871278772
50 52 0.651037481959735 0.004078507211046 1.000000000000000 0.000003181688248
51 53 0.651037480223428 0.002008470748877 1.000000000000000 0.000002052824951
52 54 0.651037479892180 0.000836856239934 1.000000000000000 0.000001711240527
53 55 0.651037479552423 0.000836856239934 1.000000000000000 0.000000569840889
Convergence criteria met.
After: gradient norm = 5.698408890195822E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2628,-0.2628}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-1.5519,0.6259,-1.0016,-0.7132,-1.4092,-1.2472,0.8743,-0.8596,-0.9383,1.0306,-0.8041,-1.9300,-1.4756,1.4411,-1.3584,-1.2488,-0.3104,0.6295,-1.4420,-1.5188,-1.3444,0.7898,-1.8241,-0.2631,-1.2582,1.4777,-1.5871,-1.2742,-1.1030,-0.8844,-1.5773,0.9230,0.2696,-1.3704,-0.5986,-0.9424,-1.5211,-0.6375,0.3865,-0.8696,-0.6817,-0.2224,-1.3334,-0.4042,-1.7174,-0.8814,1.1538,-1.1967,-1.1562,-1.2730,0.5811,-0.7937,-0.9786,-0.3027,-1.2602,-0.0993}
Activity(exp=0): {-0.0000,-2.6417}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID improve.
informationThreshold = 0.1
>>> Information used for optimizeSizeHeuristic: I[0] = 0.5055631153542964, I[1] = 0.6978790035202109, I[k-2] = 0.47627229900246965, I[k-1] = 0.1455411674120446
Suggested variations:
key=16;8;3, description = Expands: deltaLeft = 1, deltaRight = 1, deltaFlank = 1.
> Optimizing variation "Expands: deltaLeft = 1, deltaRight = 1, deltaFlank = 1." (component1-2-variation6).
>> Starting new optimization: component1-2-variation6. (2021-05-21 12:24:41.019).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[66,67]}],"bindingModeInteractions":[],"bindingModes":[{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63],"activity":[[64,65]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6528265927499706
gradient = {0.0004,0.0012,-0.0028,0.0012,0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0003,-0.0007,0.0001,0.0003,-0.0000,-0.0000,0.0000,-0.0000}
gradient norm = 0.0033965379414558085
Starting Function Value: 0.6528265927499706
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 2 0.651093512662269 1.000000000000000 294.41743835529910 0.005119731703580
2 4 0.651056607145145 0.025340392445830 0.034770043733699 0.003117778468326
3 5 0.651036771975915 0.032552881595965 1.000000000000000 0.002350853621587
4 6 0.650999776292567 0.065259430382565 1.000000000000000 0.001029307456255
5 7 0.650989883983306 0.014057284332752 1.000000000000000 0.000981155194276
6 8 0.650935914115252 0.123424747552227 1.000000000000000 0.000493624168406
7 9 0.650924422138436 0.050276494176231 1.000000000000000 0.000292926470848
8 10 0.650915678971056 0.068593960319537 1.000000000000000 0.000163975223859
9 11 0.650912457259515 0.038204223643290 1.000000000000000 0.000150436003032
10 12 0.650909225141533 0.055571635546549 1.000000000000000 0.000104856058088
11 13 0.650908137546609 0.050086601361572 1.000000000000000 0.000127114928495
12 14 0.650907440303564 0.016051908098248 1.000000000000000 0.000063920374207
13 15 0.650907146628593 0.012003292454916 1.000000000000000 0.000042309425973
14 16 0.650906868280136 0.016001580633177 1.000000000000000 0.000038644016238
15 17 0.650906558678054 0.021640972108658 1.000000000000000 0.000034052899662
16 18 0.650906315533801 0.023535486435419 1.000000000000000 0.000018296198845
17 19 0.650906261677661 0.012602619268206 1.000000000000000 0.000014093680332
18 20 0.650906237921078 0.003037719093125 1.000000000000000 0.000006928716770
19 21 0.650906226950346 0.003097094367823 1.000000000000000 0.000005012018816
20 22 0.650906214826292 0.004743770169780 1.000000000000000 0.000005626039433
21 23 0.650906193894044 0.009114184129548 1.000000000000000 0.000007574409367
22 24 0.650906156633292 0.019521702374634 1.000000000000000 0.000009826253895
23 25 0.650906099455891 0.038128755628704 1.000000000000000 0.000018948995694
24 26 0.650905999880989 0.048479805759557 1.000000000000000 0.000018396176930
25 27 0.650905668241719 0.171342825430880 1.000000000000000 0.000025516103780
26 28 0.650905189488911 0.278013944254309 1.000000000000000 0.000028766887897
27 29 0.650904565233170 0.379030931647683 1.000000000000000 0.000047910374120
28 30 0.650903882093857 0.445089127998489 1.000000000000000 0.000030459114580
29 31 0.650903437638822 0.266698841655351 1.000000000000000 0.000026682564333
30 33 0.650903308697137 0.085787859632908 0.479234247231073 0.000021391393447
31 34 0.650903207964619 0.015656367609784 1.000000000000000 0.000009546781570
32 35 0.650903189723832 0.018158232297858 1.000000000000000 0.000005055403646
33 36 0.650903179102130 0.004421636979379 1.000000000000000 0.000002848054663
34 37 0.650903175207584 0.014712039494780 1.000000000000000 0.000001944520383
35 38 0.650903174938723 0.004696174857299 1.000000000000000 0.000000991737495
36 39 0.650903174868475 0.004696174857299 1.000000000000000 0.000000265092063
Convergence criteria met.
After: gradient norm = 2.6509206268689784E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.2609,-0.2609}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.1118}
Binding mode 1:
---------------
Mononucleotide: {-0.6613,-0.9734,0.2859,-1.0432,-1.4696,0.6877,-0.9404,-0.6692,-1.3418,-1.2343,0.9107,-0.7260,-0.8227,1.0147,-0.8025,-1.7810,-1.3645,1.5059,-1.4154,-1.1175,-0.2827,0.6566,-1.2785,-1.4869,-1.2542,0.8779,-1.8463,-0.1688,-1.1787,1.5606,-1.6027,-1.1707,-1.0060,-0.8552,-1.5013,0.9710,0.3124,-1.2660,-0.5588,-0.8791,-1.4652,-0.5452,0.4061,-0.7871,-0.6732,-0.1331,-1.3038,-0.2814,-1.6703,-0.8951,1.2535,-1.0796,-1.1219,-1.1936,0.6433,-0.7193,-0.9391,-0.2371,-1.1841,-0.0312,-0.6777,-0.3762,-0.6483,-0.6897}
Activity(exp=0): {0.0000,-2.3915}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
The Likelihood DID NOT improve. Discarding fit component1-2-variation6.
informationThreshold = 0.1
>>> Information used for optimizeSizeHeuristic: I[0] = 0.5055631153542964, I[1] = 0.6978790035202109, I[k-2] = 0.47627229900246965, I[k-1] = 0.1455411674120446
> No varitions possible for Binding mode 1.
> Optimizing the full model (component1-4-all).
>> Starting new optimization: component1-4-all. (2021-05-21 12:25:11.618).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[60,61]}],"bindingModeInteractions":[],"bindingModes":[{"mononucleotide":[],"activity":[[0,1]]},{"mononucleotide":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57],"activity":[[58,59]]},{}]}
Value and gradient before optimization:
=======================================
value = 0.6510374795524227
gradient = {-0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,-0.0000}
gradient norm = 5.092005097618619E-6
Starting Function Value: 0.6510374795524227
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.651037479483919 0.000025084156763 4.926184534867677 0.000007149373354
2 4 0.651037479390486 0.000024222059147 1.000000000000000 0.000007290986764
3 5 0.651037477438179 0.000664699393179 1.000000000000000 0.000014240279972
4 6 0.651037474244600 0.001287646192894 1.000000000000000 0.000024162994079
5 7 0.651037464558140 0.004335849277443 1.000000000000000 0.000043001032098
6 8 0.651037445622260 0.009239581330947 1.000000000000000 0.000062272658766
7 9 0.651037413418989 0.017054184638272 1.000000000000000 0.000071440111358
8 10 0.651037365514541 0.025128374747235 1.000000000000000 0.000069109524183
9 11 0.651037296941344 0.036675087237673 1.000000000000000 0.000028813908687
10 12 0.651037237190207 0.032993324112453 1.000000000000000 0.000040973167089
11 13 0.651037194285562 0.019491296498307 1.000000000000000 0.000075473490411
12 14 0.651037136474777 0.024501145290347 1.000000000000000 0.000095373894166
13 15 0.651037033109586 0.046089625214328 1.000000000000000 0.000096081851941
14 16 0.651036708315131 0.161791119026590 1.000000000000000 0.000123247379132
15 17 0.651036338087196 0.219934243166275 1.000000000000000 0.000095213439468
16 18 0.651036003758512 0.177092582881853 1.000000000000000 0.000085847018890
17 19 0.651035607868618 0.228190120715784 1.000000000000000 0.000095947461233
18 20 0.651035350566573 0.123400114213892 1.000000000000000 0.000121635602326
19 21 0.651034880648706 0.227278220117828 1.000000000000000 0.000116208364493
20 22 0.651034471854633 0.228600510692644 1.000000000000000 0.000074865662996
21 23 0.651034229986896 0.150211999390732 1.000000000000000 0.000064712823922
22 24 0.651034138546086 0.045529017799042 1.000000000000000 0.000051510168392
23 25 0.651034087441293 0.012938487316821 1.000000000000000 0.000050416975606
24 26 0.651034002127993 0.034287352323441 1.000000000000000 0.000037389418054
25 27 0.651033963211325 0.029419523738481 1.000000000000000 0.000013498242909
26 28 0.651033951241068 0.010797955467293 1.000000000000000 0.000017889161659
27 29 0.651033933289312 0.013894634447184 1.000000000000000 0.000022162417579
28 30 0.651033913108693 0.012742652347966 1.000000000000000 0.000018056023311
29 31 0.651033892122983 0.010805009561091 1.000000000000000 0.000017165123186
30 32 0.651033884601642 0.003195211112155 1.000000000000000 0.000006008292494
31 33 0.651033883265461 0.001319540246157 1.000000000000000 0.000004881500928
32 34 0.651033881774056 0.000791355199342 1.000000000000000 0.000004412495775
33 35 0.651033878528630 0.002656785760631 1.000000000000000 0.000006977203910
34 36 0.651033877644308 0.001999707696422 1.000000000000000 0.000001787632449
35 37 0.651033877492280 0.000784285939201 1.000000000000000 0.000001599682837
36 38 0.651033877044313 0.000754650446793 1.000000000000000 0.000001632400155
37 39 0.651033876622345 0.000816660125174 1.000000000000000 0.000001246825730
38 40 0.651033876533203 0.000816660125174 1.000000000000000 0.000000837236118
Convergence criteria met.
After: gradient norm = 8.372361176045042E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {0.9861,-0.9861}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {0.0000,1.3348}
Binding mode 1:
---------------
Mononucleotide: {-1.4720,0.7061,-0.9217,-0.6332,-1.3293,-1.1670,0.9548,-0.7793,-0.8581,1.1112,-0.7239,-1.8500,-1.3953,1.5220,-1.2788,-1.1687,-0.2302,0.7100,-1.3618,-1.4387,-1.2645,0.8704,-1.7441,-0.1826,-1.1788,1.5586,-1.5064,-1.1942,-1.0229,-0.8042,-1.4973,1.0035,0.3500,-1.2902,-0.5184,-0.8622,-1.4410,-0.5573,0.4669,-0.7894,-0.6015,-0.1421,-1.2533,-0.3239,-1.6373,-0.8012,1.2344,-1.1167,-1.0761,-1.1929,0.6616,-0.7135,-0.8986,-0.2227,-1.1803,-0.0192}
Activity(exp=0): {-0.0000,-2.3208}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {0.0000,0.0000}
==================================
== Starts fiting Binding mode 2 ==
==================================
> Optimizing h (component2-0-h).
>> Starting new optimization: component2-0-h. (2021-05-21 12:25:41.671).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[0,1]}],"bindingModeInteractions":[],"bindingModes":[{},{},{}]}
Value and gradient before optimization:
=======================================
value = 0.8299213560014436
gradient = {-0.2919,0.2919}
gradient norm = 0.4127894975097437
Starting Function Value: 0.8299213560014436
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 2 0.645068358175293 1.000000000000000 2.422542254666728 0.051115958649277
2 3 0.642214394244131 0.110186155326776 1.000000000000000 0.000399179102897
3 4 0.642214223966351 0.000867247704377 1.000000000000000 0.000006508840106
4 5 0.642214223921075 0.000867247704377 1.000000000000000 0.000000000719360
Convergence criteria met.
After: gradient norm = 7.193604935291243E-10
>>> Parameters after optimization
Count Table 0:
---------------
h: {1.6147,-1.6147}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {0.0000,1.3348}
Binding mode 1:
---------------
Mononucleotide: {-1.4720,0.7061,-0.9217,-0.6332,-1.3293,-1.1670,0.9548,-0.7793,-0.8581,1.1112,-0.7239,-1.8500,-1.3953,1.5220,-1.2788,-1.1687,-0.2302,0.7100,-1.3618,-1.4387,-1.2645,0.8704,-1.7441,-0.1826,-1.1788,1.5586,-1.5064,-1.1942,-1.0229,-0.8042,-1.4973,1.0035,0.3500,-1.2902,-0.5184,-0.8622,-1.4410,-0.5573,0.4669,-0.7894,-0.6015,-0.1421,-1.2533,-0.3239,-1.6373,-0.8012,1.2344,-1.1167,-1.0761,-1.1929,0.6616,-0.7135,-0.8986,-0.2227,-1.1803,-0.0192}
Activity(exp=0): {-0.0000,-2.3208}
Binding mode 2:
---------------
Mononucleotide: {-0.0039,-0.0028,0.0011,-0.0019,-0.0004,-0.0012,-0.0022,-0.0021,-0.0025,0.0042,-0.0043,0.0048,-0.0016,-0.0033,0.0039,-0.0038,-0.0024,0.0019,0.0019,-0.0003,0.0041,0.0037,-0.0026,-0.0039,-0.0005,-0.0021,-0.0019,-0.0005,0.0017,0.0037,0.0041,-0.0010,-0.0012,-0.0026,-0.0032,0.0046,-0.0042,0.0013,0.0045,-0.0033,-0.0016,0.0046,0.0014,0.0047,-0.0020,0.0022,0.0039,-0.0021}
Activity(exp=0): {-2.7833,-1.5894}
> Initial optimization (component2-1-f0).
>> Starting new optimization: component2-1-f0. (2021-05-21 12:25:45.865).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]}]}
Value and gradient before optimization:
=======================================
value = 0.6529489308064048
gradient = {0.0018,0.0019,0.0015,0.0018,0.0017,0.0019,0.0016,0.0019,0.0017,0.0017,0.0017,0.0019,0.0018,0.0017,0.0015,0.0020,0.0018,0.0018,0.0016,0.0018,0.0019,0.0016,0.0016,0.0019,0.0019,0.0016,0.0016,0.0019,0.0018,0.0016,0.0018,0.0018,0.0020,0.0015,0.0017,0.0018,0.0019,0.0017,0.0017,0.0017,0.0018,0.0016,0.0019,0.0017,0.0018,0.0015,0.0019,0.0018,-0.0000,0.0070,0.0000,-0.0000}
gradient norm = 0.014032787887939768
Starting Function Value: 0.6529489308064048
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.652742714635243 0.036331322823293 2.589030997505289 0.016726846065271
2 4 0.652520320073595 0.018394153136237 1.000000000000000 0.013844724937396
3 5 0.650045584699090 0.510398933266751 1.000000000000000 0.049292989890947
4 6 0.649094267757399 0.053414685612467 1.000000000000000 0.025102292106434
5 7 0.647694338614325 0.185233177716391 1.000000000000000 0.010765185874025
6 8 0.646732554020172 0.350160232557090 1.000000000000000 0.023129592093875
7 9 0.646206173936925 0.052480681717951 1.000000000000000 0.008974063716801
8 10 0.645772998842800 0.213132235099760 1.000000000000000 0.008203579418546
9 11 0.645518434745093 0.145864871032800 1.000000000000000 0.003589236607716
10 12 0.645361020125179 0.205217651128190 1.000000000000000 0.005834434899110
11 13 0.645231732018413 0.192409197632462 1.000000000000000 0.001727225403641
12 14 0.645189396241273 0.243282944079761 1.000000000000000 0.004384082507276
13 15 0.645166322775618 0.020750370614161 1.000000000000000 0.001022547190897
14 16 0.645151729406977 0.113503372298750 1.000000000000000 0.000172824937903
15 17 0.645145558994413 0.119663225386578 1.000000000000000 0.000215955269147
16 18 0.645143747381463 0.048576181310925 1.000000000000000 0.000200261233687
17 19 0.645142336714285 0.051257351304263 1.000000000000000 0.000519402326919
18 20 0.645140975769341 0.042054614384851 1.000000000000000 0.000718140775229
19 21 0.645137344166226 0.087822718165190 1.000000000000000 0.001048715252372
20 22 0.645130453011988 0.145442851711732 1.000000000000000 0.001277419237353
21 23 0.645125037123055 0.153642284224389 1.000000000000000 0.000572339489524
22 24 0.645121009666786 0.102374128372563 1.000000000000000 0.000417764078451
23 25 0.645120237641417 0.077175320053201 1.000000000000000 0.000228404561560
24 26 0.645120060535877 0.019256637415959 1.000000000000000 0.000023257498534
25 27 0.645120056642168 0.001789568698796 1.000000000000000 0.000011921585937
26 28 0.645120055099119 0.000546930914467 1.000000000000000 0.000016072957143
27 29 0.645120046695683 0.002163908134732 1.000000000000000 0.000038309283982
28 30 0.645120029581447 0.003517722372204 1.000000000000000 0.000068309730275
29 31 0.645119983792381 0.008591382235442 1.000000000000000 0.000117106416040
30 32 0.645119888680880 0.017689353723357 1.000000000000000 0.000170598565453
31 33 0.645119732826448 0.030551468210215 1.000000000000000 0.000191025720765
32 34 0.645119584361416 0.030757141484245 1.000000000000000 0.000127039114156
33 35 0.645119524754873 0.013057046983542 1.000000000000000 0.000031255792893
34 36 0.645119516609440 0.003160133322289 1.000000000000000 0.000012576448038
35 37 0.645119515071754 0.001795253762727 1.000000000000000 0.000019014571866
36 38 0.645119511666592 0.002270631992848 1.000000000000000 0.000026074537865
37 39 0.645119500136210 0.004406916299867 1.000000000000000 0.000039998471564
38 40 0.645119470854314 0.007551246287020 1.000000000000000 0.000061306964188
39 41 0.645119396057263 0.017798172066992 1.000000000000000 0.000093710203268
40 42 0.645119221388003 0.045633932357448 1.000000000000000 0.000135910633437
41 43 0.645118868819957 0.105206539917950 1.000000000000000 0.000172710513832
42 44 0.645118348190540 0.180213121123663 1.000000000000000 0.000162407254639
43 45 0.645117608640206 0.237119298775237 1.000000000000000 0.000124387354924
44 46 0.645116589875411 0.388953354430783 1.000000000000000 0.000030202565302
45 47 0.645116096706569 0.158109744018232 1.000000000000000 0.000089616196876
46 48 0.645115504891717 0.148893929849392 1.000000000000000 0.000123585081799
47 49 0.645114787259757 0.194563438253137 1.000000000000000 0.000125202053442
48 50 0.645112617684695 0.688247344492317 1.000000000000000 0.000023300945833
49 51 0.645111101327334 0.728410603094684 1.000000000000000 0.000069129971256
50 52 0.645110890869968 0.060876145088267 1.000000000000000 0.000041350616915
51 53 0.645110786813937 0.038292262919449 1.000000000000000 0.000013470989771
52 54 0.645110721821780 0.025276146539785 1.000000000000000 0.000022898655545
53 55 0.645110630522760 0.023932976987912 1.000000000000000 0.000049754695793
54 56 0.645110537063143 0.043937776677063 1.000000000000000 0.000064427231757
55 57 0.645110440362202 0.071684603387330 1.000000000000000 0.000054329632027
56 58 0.645110368039055 0.065805401247825 1.000000000000000 0.000023172279110
57 59 0.645110346894076 0.019149721003161 1.000000000000000 0.000003146205306
58 60 0.645110343652874 0.008135310554104 1.000000000000000 0.000003863304573
59 61 0.645110342353254 0.005604479697226 1.000000000000000 0.000003605156970
60 62 0.645110334226100 0.006897495428169 1.000000000000000 0.000001778748947
61 63 0.645110329254585 0.008337530561301 1.000000000000000 0.000000705227594
62 64 0.645110328767923 0.003151853052538 1.000000000000000 0.000000314525876
63 65 0.645110328512261 0.002491373458580 1.000000000000000 0.000000306428254
64 66 0.645110328456168 0.002491373458580 1.000000000000000 0.000000119423299
Convergence criteria met.
After: gradient norm = 1.1942329880940398E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {1.0302,-1.0302}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {0.0000,1.3348}
Binding mode 1:
---------------
Mononucleotide: {-1.4720,0.7061,-0.9217,-0.6332,-1.3293,-1.1670,0.9548,-0.7793,-0.8581,1.1112,-0.7239,-1.8500,-1.3953,1.5220,-1.2788,-1.1687,-0.2302,0.7100,-1.3618,-1.4387,-1.2645,0.8704,-1.7441,-0.1826,-1.1788,1.5586,-1.5064,-1.1942,-1.0229,-0.8042,-1.4973,1.0035,0.3500,-1.2902,-0.5184,-0.8622,-1.4410,-0.5573,0.4669,-0.7894,-0.6015,-0.1421,-1.2533,-0.3239,-1.6373,-0.8012,1.2344,-1.1167,-1.0761,-1.1929,0.6616,-0.7135,-0.8986,-0.2227,-1.1803,-0.0192}
Activity(exp=0): {-0.0000,-2.3208}
Binding mode 2:
---------------
Mononucleotide: {-0.2105,-0.4230,-0.4324,-0.1922,-0.1842,-0.4382,-0.4399,-0.1958,-0.1743,-0.4518,-0.4421,-0.1898,-0.1875,-0.4474,-0.4524,-0.1707,-0.1522,-0.4827,-0.4689,-0.1542,-0.1576,-0.4716,-0.4476,-0.1812,-0.1811,-0.4475,-0.4718,-0.1576,-0.1541,-0.4690,-0.4826,-0.1523,-0.1709,-0.4524,-0.4473,-0.1874,-0.1899,-0.4422,-0.4518,-0.1742,-0.1957,-0.4399,-0.4381,-0.1843,-0.1922,-0.4323,-0.4231,-0.2105}
Activity(exp=0): {0.0004,-1.2578}
Suggested variations:
key=12;5;0, description = Initial model.
> Optimizing variation "Initial model." (component2-2-variation0).
>> Starting new optimization: component2-2-variation0. (2021-05-21 12:26:54.2).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]}]}
Value and gradient before optimization:
=======================================
value = 0.6451103284561677
gradient = {0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000}
gradient norm = 1.1942329880946515E-7
Already at minimum!
After: gradient norm = 1.1942329880946515E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {1.0302,-1.0302}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {0.0000,1.3348}
Binding mode 1:
---------------
Mononucleotide: {-1.4720,0.7061,-0.9217,-0.6332,-1.3293,-1.1670,0.9548,-0.7793,-0.8581,1.1112,-0.7239,-1.8500,-1.3953,1.5220,-1.2788,-1.1687,-0.2302,0.7100,-1.3618,-1.4387,-1.2645,0.8704,-1.7441,-0.1826,-1.1788,1.5586,-1.5064,-1.1942,-1.0229,-0.8042,-1.4973,1.0035,0.3500,-1.2902,-0.5184,-0.8622,-1.4410,-0.5573,0.4669,-0.7894,-0.6015,-0.1421,-1.2533,-0.3239,-1.6373,-0.8012,1.2344,-1.1167,-1.0761,-1.1929,0.6616,-0.7135,-0.8986,-0.2227,-1.1803,-0.0192}
Activity(exp=0): {-0.0000,-2.3208}
Binding mode 2:
---------------
Mononucleotide: {-0.2105,-0.4230,-0.4324,-0.1922,-0.1842,-0.4382,-0.4399,-0.1958,-0.1743,-0.4518,-0.4421,-0.1898,-0.1875,-0.4474,-0.4524,-0.1707,-0.1522,-0.4827,-0.4689,-0.1542,-0.1576,-0.4716,-0.4476,-0.1812,-0.1811,-0.4475,-0.4718,-0.1576,-0.1541,-0.4690,-0.4826,-0.1523,-0.1709,-0.4524,-0.4473,-0.1874,-0.1899,-0.4422,-0.4518,-0.1742,-0.1957,-0.4399,-0.4381,-0.1843,-0.1922,-0.4323,-0.4231,-0.2105}
Activity(exp=0): {0.0004,-1.2578}
The Likelihood DID NOT improve. Discarding fit component2-2-variation0.
Suggested variations:
key=12;6;0, description = Increases flank length.
> Optimizing variation "Increases flank length." (component2-2-variation1).
>> Starting new optimization: component2-2-variation1. (2021-05-21 12:26:55.171).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[50,51]}],"bindingModeInteractions":[],"bindingModes":[{},{},{"mononucleotide":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"activity":[[48,49]]}]}
Value and gradient before optimization:
=======================================
value = 0.6451166595223542
gradient = {0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0001,-0.0010,0.0010}
gradient norm = 0.0014151198596026354
Starting Function Value: 0.6451166595223542
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.645114474571872 0.003024219441387 2.137076531620948 0.000041296510137
2 4 0.645114471760276 0.000092010809694 1.000000000000000 0.000028860652202
3 5 0.645114467436389 0.000190283096238 1.000000000000000 0.000040172662165
4 6 0.645114453497139 0.000741376313774 1.000000000000000 0.000087819383787
5 7 0.645114422320808 0.001881069266929 1.000000000000000 0.000157938392525
6 8 0.645114352367007 0.004647842034248 1.000000000000000 0.000242262495829
7 9 0.645114237396400 0.008534755546017 1.000000000000000 0.000276657462186
8 10 0.645114125832931 0.009532627494516 1.000000000000000 0.000177007683381
9 11 0.645114091598830 0.003254470939815 1.000000000000000 0.000051383708799
10 12 0.645114086496312 0.000763780048586 1.000000000000000 0.000010444274836
11 13 0.645114085707873 0.000698103089775 1.000000000000000 0.000016405077035
12 14 0.645114084751364 0.000364914146371 1.000000000000000 0.000019730008035
13 15 0.645114077636671 0.001708260410505 1.000000000000000 0.000035872657803
14 16 0.645114062846452 0.002766441346740 1.000000000000000 0.000056620930446
15 17 0.645114026991425 0.006698186453418 1.000000000000000 0.000084475751011
16 18 0.645113965742819 0.012979589198306 1.000000000000000 0.000099745517917
17 19 0.645113897873511 0.017403327841809 1.000000000000000 0.000074603701662
18 20 0.645113869115347 0.009789929793203 1.000000000000000 0.000024796237092
19 21 0.645113865143322 0.001960324198229 1.000000000000000 0.000003415207488
20 22 0.645113864814550 0.000790354466961 1.000000000000000 0.000004793486794
21 23 0.645113864450214 0.000458950120368 1.000000000000000 0.000005779581133
22 24 0.645113862131908 0.001747852205906 1.000000000000000 0.000009535145781
23 25 0.645113857496687 0.002681228135399 1.000000000000000 0.000013519308889
24 26 0.645113849537368 0.005041931124784 1.000000000000000 0.000014734255528
25 27 0.645113840340624 0.007678533662294 1.000000000000000 0.000007757955900
26 28 0.645113837882012 0.004360974314962 1.000000000000000 0.000001266060352
27 29 0.645113837535276 0.000822902718910 1.000000000000000 0.000002752599090
28 30 0.645113837067952 0.000925328906782 1.000000000000000 0.000004312807036
29 31 0.645113836212361 0.001609503933449 1.000000000000000 0.000005515407870
30 32 0.645113834984594 0.002650412831256 1.000000000000000 0.000004861935121
31 33 0.645113834035871 0.002513538021794 1.000000000000000 0.000001897395229
32 34 0.645113833814939 0.001080264773596 1.000000000000000 0.000000654145832
33 35 0.645113833769217 0.000268155223169 1.000000000000000 0.000001169016460
34 36 0.645113833675544 0.000528309826252 1.000000000000000 0.000001761077680
35 37 0.645113833538010 0.000821096069309 1.000000000000000 0.000001926974006
36 38 0.645113833354561 0.001289523396103 1.000000000000000 0.000001071043452
37 39 0.645113833306811 0.001289523396103 1.000000000000000 0.000000139615324
Convergence criteria met.
After: gradient norm = 1.3961532410889753E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {1.0304,-1.0304}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {0.0000,1.3348}
Binding mode 1:
---------------
Mononucleotide: {-1.4720,0.7061,-0.9217,-0.6332,-1.3293,-1.1670,0.9548,-0.7793,-0.8581,1.1112,-0.7239,-1.8500,-1.3953,1.5220,-1.2788,-1.1687,-0.2302,0.7100,-1.3618,-1.4387,-1.2645,0.8704,-1.7441,-0.1826,-1.1788,1.5586,-1.5064,-1.1942,-1.0229,-0.8042,-1.4973,1.0035,0.3500,-1.2902,-0.5184,-0.8622,-1.4410,-0.5573,0.4669,-0.7894,-0.6015,-0.1421,-1.2533,-0.3239,-1.6373,-0.8012,1.2344,-1.1167,-1.0761,-1.1929,0.6616,-0.7135,-0.8986,-0.2227,-1.1803,-0.0192}
Activity(exp=0): {-0.0000,-2.3208}
Binding mode 2:
---------------
Mononucleotide: {-0.2126,-0.4286,-0.4491,-0.1789,-0.1925,-0.4541,-0.4263,-0.1964,-0.1800,-0.4544,-0.4474,-0.1875,-0.1691,-0.4548,-0.4688,-0.1766,-0.1514,-0.4754,-0.4652,-0.1772,-0.1684,-0.4664,-0.4547,-0.1797,-0.1797,-0.4547,-0.4664,-0.1684,-0.1772,-0.4652,-0.4754,-0.1514,-0.1766,-0.4688,-0.4548,-0.1691,-0.1875,-0.4474,-0.4544,-0.1800,-0.1964,-0.4263,-0.4541,-0.1926,-0.1789,-0.4491,-0.4286,-0.2126}
Activity(exp=0): {0.0004,-1.2690}
The Likelihood DID NOT improve. Discarding fit component2-2-variation1.
informationThreshold = 0.1
>>> Information used for optimizeSizeHeuristic: I[0] = 0.009224243494022066, I[1] = 0.011115448133988237, I[k-2] = 0.011110077864986079, I[k-1] = 0.009219867465532383
> No varitions possible for Binding mode 2.
> Optimizing the full model (component2-4-all).
>> Starting new optimization: component2-4-all. (2021-05-21 12:27:37.032).
>>> Packing before optimization
Packing: {"enrichmentModel":[{}],"countTable":[{"h":[110,111]}],"bindingModeInteractions":[],"bindingModes":[{"mononucleotide":[],"activity":[[0,1]]},{"mononucleotide":[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57],"activity":[[58,59]]},{"mononucleotide":[60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107],"activity":[[108,109]]}]}
Value and gradient before optimization:
=======================================
value = 0.6616770600855362
gradient = {0.0000,0.0013,-0.0001,-0.0009,-0.0001,-0.0002,-0.0001,-0.0001,-0.0009,-0.0002,-0.0001,-0.0009,-0.0001,-0.0002,-0.0000,-0.0012,-0.0000,-0.0000,-0.0003,-0.0008,-0.0001,-0.0001,-0.0001,-0.0009,-0.0001,-0.0003,-0.0000,-0.0012,-0.0000,-0.0000,-0.0001,-0.0002,-0.0001,-0.0009,-0.0006,-0.0002,-0.0003,-0.0002,-0.0001,-0.0003,-0.0007,-0.0002,-0.0004,-0.0005,-0.0001,-0.0003,-0.0000,-0.0003,-0.0009,-0.0001,-0.0002,-0.0001,-0.0008,-0.0002,-0.0002,-0.0005,-0.0002,-0.0005,-0.0000,-0.0013,0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000,0.0000,-0.0000,0.0000,-0.0000,-0.0000,-0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,-0.0000}
gradient norm = 0.0038911222520860945
Starting Function Value: 0.6616770600855362
Iterations Fnc. Calls Likelihood Distance Moved Step Alpha Gradient Norm
1 3 0.661596110255145 0.037256116296782 9.574645534924557 0.001844905049118
2 5 0.661592200116615 0.004675953730109 0.216754745324876 0.000593140187134
3 6 0.661591328204698 0.003673292973181 1.000000000000000 0.000400523669533
4 7 0.661590213586897 0.003072692137477 1.000000000000000 0.000409613500901
5 8 0.661555590620162 0.133957742172572 1.000000000000000 0.002849539898506
6 9 0.661534522948218 0.134173108433410 1.000000000000000 0.005267315688579
7 10 0.661504086924973 0.048182653303410 1.000000000000000 0.002848247395103
8 11 0.661489407882919 0.057569614102983 1.000000000000000 0.000648221584714
9 12 0.661488218312861 0.010483102370698 1.000000000000000 0.000396001251479
10 13 0.661487191055155 0.037134172700039 1.000000000000000 0.000454603910840
11 14 0.661477004881346 0.033256514182187 1.000000000000000 0.000626900027909
12 15 0.661468127945192 0.072708240621215 1.000000000000000 0.000598432077428
13 16 0.661466078957644 0.008571574519228 1.000000000000000 0.000348965616438
14 17 0.661456028960605 0.062820456114295 1.000000000000000 0.001439954924239
15 18 0.661435539729048 0.168854755032341 1.000000000000000 0.001149673156448
16 20 0.661427314700324 0.098916926788895 0.208416094399579 0.000692893400796
17 21 0.661421569211717 0.108930475322256 1.000000000000000 0.001621017286578
18 22 0.661417828663529 0.030933134192853 1.000000000000000 0.000369596636936
19 23 0.661411448138908 0.023045032329186 1.000000000000000 0.000279062207546
20 24 0.661400830123135 0.126279508201776 1.000000000000000 0.001610254063233
21 25 0.661399654525490 0.014560281115564 1.000000000000000 0.000578624354443
22 26 0.661398526174690 0.015030573046203 1.000000000000000 0.000409296503670
23 27 0.661394246477886 0.080784350685622 1.000000000000000 0.000724343134601
24 28 0.661390703343839 0.048158349498009 1.000000000000000 0.000754147097200
25 29 0.661382083001631 0.097231751222810 1.000000000000000 0.000998991885700
26 30 0.661375591707675 0.085139865428459 1.000000000000000 0.000900048056746
27 32 0.661372500600968 0.052527672620228 0.169271015376563 0.000606802269154
28 33 0.661370808770298 0.060908129908212 1.000000000000000 0.001627370442328
29 34 0.661369128186966 0.013499996069354 1.000000000000000 0.000691646391844
30 35 0.661367385535213 0.029603279893474 1.000000000000000 0.000425858370713
31 36 0.661365020542680 0.069214420379045 1.000000000000000 0.000570399834765
32 37 0.661362003434951 0.033893395264626 1.000000000000000 0.000403178497257
33 39 0.661355777934042 0.084126778587629 0.433359392932635 0.000975412623812
34 40 0.661345364129827 0.280832067498263 1.000000000000000 0.003998558092597
35 42 0.661335873608184 0.038240311206188 0.346685891806331 0.000709555872239
36 43 0.661329679096381 0.026788196437268 1.000000000000000 0.000584911145717
37 44 0.661303490879953 0.089213377274139 1.000000000000000 0.000594788582315
38 46 0.661261611372600 0.205341769874408 0.310334535301182 0.003150198297004
39 48 0.661231697384150 0.162288331139041 0.447136406419269 0.004534866400701
40 49 0.661212214463941 0.160184294182571 1.000000000000000 0.001125601823410
41 50 0.661194402978255 0.152052380076787 1.000000000000000 0.003161064382035
42 51 0.661184275827010 0.076555443289420 1.000000000000000 0.001115254454706
43 52 0.661179758270296 0.037784956899226 1.000000000000000 0.000755317248845
44 53 0.661175123179784 0.051565841677224 1.000000000000000 0.000512295558678
45 54 0.661168846023367 0.037843328621776 1.000000000000000 0.000417465830910
46 55 0.661148104532393 0.130939029806152 1.000000000000000 0.000298616429021
47 56 0.661128500149269 0.130667754287870 1.000000000000000 0.000623324784267
48 57 0.661111820535858 0.191493498843623 1.000000000000000 0.000699397181760
49 58 0.661101520323034 0.109696648787798 1.000000000000000 0.002123623780749
50 59 0.661093793788613 0.113817057071475 1.000000000000000 0.000258522946633
51 60 0.661092448286678 0.028507852441000 1.000000000000000 0.000705552221316
52 61 0.661091877233942 0.012559590207507 1.000000000000000 0.000588955542834
53 62 0.661089841157081 0.025624949481624 1.000000000000000 0.000356593416539
54 63 0.661086347040243 0.048741345543613 1.000000000000000 0.000208278025114
55 64 0.661083206683840 0.059907260322203 1.000000000000000 0.000276915318850
56 65 0.661078260398031 0.062399518269372 1.000000000000000 0.000185131723275
57 66 0.661072628150393 0.101412296327507 1.000000000000000 0.000608825020447
58 67 0.661070985429711 0.026190818641353 1.000000000000000 0.000386860396732
59 68 0.661069569182902 0.044263039354054 1.000000000000000 0.000767420465306
60 69 0.661068919236884 0.015102931152842 1.000000000000000 0.000177698639900
61 70 0.661068273123398 0.014238612964430 1.000000000000000 0.000155999733228
62 71 0.661066850960230 0.040806791944429 1.000000000000000 0.000257390883968
63 72 0.661065036612946 0.039794223740976 1.000000000000000 0.000277825747093
64 73 0.661059392371291 0.116087387524852 1.000000000000000 0.000453366556853
65 74 0.661056291116895 0.064148374337688 1.000000000000000 0.000384736090591
66 75 0.661055640122038 0.025101821661883 1.000000000000000 0.000211809580542
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240 263 0.660941233409063 0.004805579673540 0.322728952491728 0.000007099127115
241 264 0.660941232680020 0.002551195699284 1.000000000000000 0.000003916031905
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243 266 0.660941232128832 0.000448632595154 1.000000000000000 0.000001557259722
244 267 0.660941232001754 0.000655373500438 1.000000000000000 0.000001948998688
245 268 0.660941231828069 0.001410887113329 1.000000000000000 0.000001512170153
246 270 0.660941231759273 0.000727992315433 0.380564572735064 0.000002364910067
247 271 0.660941231645956 0.000727992315433 1.000000000000000 0.000000814558580
Convergence criteria met.
After: gradient norm = 8.145585800677857E-7
>>> Parameters after optimization
Count Table 0:
---------------
h: {2.4069,-2.4069}
Binding mode 0:
---------------
Mononucleotide: {}
Activity(exp=0): {-0.0000,-0.7879}
Binding mode 1:
---------------
Mononucleotide: {-1.2367,0.8345,-0.6760,-0.4776,-1.1032,-0.9228,1.0804,-0.6102,-0.6624,1.2356,-0.5078,-1.6212,-1.1728,1.6043,-0.9980,-0.9893,-0.0750,0.8565,-1.1193,-1.2179,-1.0710,1.0063,-1.4804,-0.0107,-0.9751,1.6852,-1.2490,-1.0169,-0.8384,-0.5782,-1.2413,1.1021,0.4816,-1.0465,-0.3222,-0.6687,-1.2235,-0.3518,0.6210,-0.6014,-0.4234,0.0458,-1.0111,-0.1670,-1.4103,-0.5762,1.3474,-0.9167,-0.8686,-0.9539,0.7981,-0.5314,-0.6866,-0.0479,-0.9472,0.1260}
Activity(exp=0): {0.0000,-1.5558}
Binding mode 2:
---------------
Mononucleotide: {-0.0628,0.0020,-0.0390,0.0375,0.0668,0.0089,-0.2548,0.1168,0.0454,-0.3391,0.2691,-0.0377,-0.0111,0.1186,-0.3130,0.1432,0.5859,-0.4030,-0.2528,0.0076,-0.2136,-0.0770,0.0925,0.1359,-0.2650,-0.0271,-0.1568,0.3867,0.0561,-0.1385,0.1309,-0.1107,0.0939,0.0003,0.0433,-0.1998,-0.0963,0.5837,-0.5230,-0.0266,0.2205,-0.3142,0.2318,-0.2004,-0.1481,0.0298,0.0163,0.0397}
Activity(exp=0): {-0.0000,-0.0623}
> Optimization done.
Probound Model
±
Optimized model:
{"metadata":{"timeStamp":"2021-05-21 12:33:28.375","logLikelihoodPerRead":0.6609412316459564,"logLikelihood":78566.67484492347,"gradientCalls":789,"fitSteps":766,"regularization":0.02721635872762166,"functionCalls":0,"fitter":"proBound","fitName":"component2-4-all","fitTime":743.894,"dataLoops":789},"optimizerSetting":{"output":{"outputPath":"jobs/f2900d99a9ca","baseName":"fit"},"nThreads":4,"likelihoodThreshold":2.0E-4,"lbfgsSettings":{"memory":100,"convergence":1.0E-7,"MCSearch":true,"maxIters":500},"lambdaL2":1.0E-6,"fixedLibrarySize":false,"expBound":40,"nRetries":3,"hkSettings":{"epsilon":1.0E-7,"kickFinal":false,"fdDelta":1.0E-4,"kickAll":false,"maxIters":200,"evCutoff":1.0E-9}},"modelSettings":{"enrichmentModel":[{"variationsOptimized":false,"bindingSaturation":false,"cumulativeEnrichment":true,"concentration":1,"modelType":"SELEX","bindingModeInteractions":[],"componentName":"SELEX enrichment model 0","freezingLevel":0,"includeComponent":true,"bindingModes":[0,1,2],"variationDescription":[],"modifications":[]}],"letterOrder":"ACGT","countTable":[{"leftFlank":"ACACTCTTTCCCTACACGACGCTCTTCCGATCTTGACGTC","variationsOptimized":true,"transliterate":{"in":[],"out":[]},"variableRegionLength":30,"countTableFile":"jobs/f2900d99a9ca/countTable.0.tsv.gz","modeledColumns":[0,1],"inputFileType":"tsv.gz","nColumns":2,"rightFlank":"GACGTCAGATCGGAAGAGCTCGTATGCCGTCTTCTGCTTG","componentName":"Count table 0","freezingLevel":0,"includeComponent":true,"variationDescription":[]}],"bindingModeInteractions":[],"bindingModes":[{"variationsOptimized":true,"fitLogActivity":true,"flankLength":0,"singleStrand":false,"variationName":"0;0;0","size":0,"dinucleotideDistance":0,"componentName":"Binding mode 0","freezingLevel":0,"positionBias":false,"includeComponent":true,"variationDescription":[{"variationName":"0;0;0","descriptionString":"Initial 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Binding Mode 0
Size
0
Flank length
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Binding Mode 1
Size
14
Flank length
7
Mononucleotide (14bp)
Binding Mode 2
Size
12
Flank length
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Mononucleotide (12bp)
