Multi-parameter sensitivity analysis (MPSA) with PMC

Created: 2011-07-14 08:59:23 Last updated: 2011-07-21 10:08:07

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Exemplary multi-parameter sensitivity analysis (MPSA) experiment using Tav4SB (http://bioputer.mimuw.edu.pl/tav4sb/) WS operations. In this version of MPSA PRISM probabilistic model checking is basis of analysis of SBML model parameters space.

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Titles (2)

Descriptions (1)

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Processors (18)

Name	Type	Description
samplesNr	stringconstant	Value 400
paramCsv	stringconstant	Value k1, k3
model	stringconstant	Value $k1 s e$ $k2 es$ $k3 es$
thresholdMethod	stringconstant	Value median
setParamsRange	beanshell	Script source(new URL("http://bioputer.mimuw.edu.pl/tav4sb/workflows/setParamsRange.bsh"));
ClassifySamples	workflow
SelectParameters	workflow
CalculateSensitivity	workflow
GenerateSamples	workflow
CalculateSamplesError_PMC	workflow
rangeMul	stringconstant	Value 4
ifGeneratePlots	stringconstant	Value true
samplingMethod	stringconstant	Value LHS
scale	stringconstant	Value LIN
distribution	stringconstant	Value uniform
properties_value	stringconstant	Value R{"r1"}=? [ F (p >= 0.5 * 12) ]
getRewards	localworker	Script BufferedReader getReader (String fileUrl) throws IOException { InputStreamReader reader; try { reader = new FileReader(fileUrl); } catch (FileNotFoundException e) { // try a real URL instead URL url = new URL(fileUrl); reader = new InputStreamReader (url.openStream()); } return new BufferedReader(reader); } StringBuffer sb = new StringBuffer(4000); BufferedReader in = getReader(fileurl); String str; String lineEnding = System.getProperty("line.separator"); while ((str = in.readLine()) != null) { sb.append(str); sb.append(lineEnding); } in.close(); filecontents = sb.toString();
rewardsUrl	stringconstant	Value http://bioputer.mimuw.edu.pl/tav4sb/models/enzyme.rew

Beanshells (15)

Name	Inputs	Outputs
setParamsRange	paramXmlList multiplier	paramListXml
fromPair	pair	el1 el2
paramXmlList2selectedParamsXml	paramXmlList	selectedParamsXml
sampleXmlList2sampleListXml	sampleXmlList	sampleListXml
toPair	list1 list2	listsPair
buildXPathFilter	attrName attrValList ifQuoteVal	xpath
getSbmlParams	model	paramListXml
calculateThreshold	method numbers	threshold
classifySamples	threshold sampleList sampleErrorList	unacceptableSampleList acceptableSampleList
setSbmlParams	modelInXml paramListXml	modelOutXml
meanAbsDiff	valList1 valList2	error
pointListXmlToValuesListList	pointListXml coordinateNameList	coordinateValueListList
refPointListXmlToValuesListList	pointListXml coordinateNameList	coordinateValueListList
setConstantCompactXmlList	input	output
wrapWithResultsTag	str name	wrapped

Outputs (6)

Name	Description
paramXmlList
ecdfPlotList
paramRankingXmlList
sampleErrorList
sampleXmlList
sampleErrorThreshold

Datalinks (28)

Source	Sink
SelectParameters:paramXmlList	setParamsRange:paramXmlList
rangeMul:value	setParamsRange:multiplier
GenerateSamples:sampleXmlList	ClassifySamples:sampleList
CalculateSamplesError_PMC:sampleErrorList	ClassifySamples:sampleErrorList
thresholdMethod:value	ClassifySamples:method
paramCsv:value	SelectParameters:paramNameCsv
model:value	SelectParameters:modelXml
ClassifySamples:unacceptableSampleList	CalculateSensitivity:unacceptableSampleXmlList
SelectParameters:paramXmlList	CalculateSensitivity:paramXmlList
ClassifySamples:acceptableSampleList	CalculateSensitivity:acceptableSampleXmlList
ifGeneratePlots:value	CalculateSensitivity:ifGeneratePlots
scale:value	GenerateSamples:scale
samplesNr:value	GenerateSamples:nr
setParamsRange:paramListXml	GenerateSamples:paramListXml
samplingMethod:value	GenerateSamples:method
distribution:value	GenerateSamples:distribution
rangeMul:value	GenerateSamples:rangeMultiplier
GenerateSamples:sampleXmlList	CalculateSamplesError_PMC:sampleXmlList
properties_value:value	CalculateSamplesError_PMC:properties
model:value	CalculateSamplesError_PMC:modelXml
getRewards:filecontents	CalculateSamplesError_PMC:rewards
rewardsUrl:value	getRewards:fileurl
SelectParameters:paramXmlList	paramXmlList
CalculateSensitivity:plotList	ecdfPlotList
CalculateSensitivity:paramRankingXmlList	paramRankingXmlList
CalculateSamplesError_PMC:sampleErrorList	sampleErrorList
GenerateSamples:sampleXmlList	sampleXmlList
ClassifySamples:errorThreshold	sampleErrorThreshold

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Taverna 2

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trybik

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trybik

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Information Statistics

2289 viewings

1418 downloads

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Version History

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Multi-parameter sensitivity analysis (MPSA) of a stochastic SBML model

Created by trybik on Thursday 14 July 2011 08:59:23 (UTC)

Last edited by trybik on Thursday 14 July 2011 09:01:31 (UTC)
Multi-parameter sensitivity analysis (MPSA) with PMC

Created by trybik on Thursday 21 July 2011 10:07:16 (UTC)

Last edited by trybik on Thursday 21 July 2011 10:08:07 (UTC)

Revision comment:

upgraded parrallel jobs config

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Created: 2011-01-26 | Last updated: 2011-01-26

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Multi-parameter sensitivity analysis (MPSA) with PMC

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