Towards a rigorous assessment of systems biology models: The DREAM3 challenges

Prill, RJ; Marbach, D; Saez-Rodriguez, J; Sorger, PK; Alexopoulos, LG; Xue, X; Clarke, ND; Altan-Bonnet, G; Stolovitzky, G

dc.contributor.author	Prill, RJ	en
dc.contributor.author	Marbach, D	en
dc.contributor.author	Saez-Rodriguez, J	en
dc.contributor.author	Sorger, PK	en
dc.contributor.author	Alexopoulos, LG	en
dc.contributor.author	Xue, X	en
dc.contributor.author	Clarke, ND	en
dc.contributor.author	Altan-Bonnet, G	en
dc.contributor.author	Stolovitzky, G	en
dc.date.accessioned	2014-03-01T01:34:48Z
dc.date.available	2014-03-01T01:34:48Z
dc.date.issued	2010	en
dc.identifier.issn	1932-6203	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20863
dc.subject	System Biology	en
dc.subject.other	cytokine	en
dc.subject.other	gamma interferon	en
dc.subject.other	interleukin 1alpha	en
dc.subject.other	interleukin 6	en
dc.subject.other	lipopolysaccharide	en
dc.subject.other	phosphoprotein	en
dc.subject.other	somatomedin C	en
dc.subject.other	transforming growth factor alpha	en
dc.subject.other	tumor necrosis factor alpha	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	communicable disease	en
dc.subject.other	computer model	en
dc.subject.other	controlled study	en
dc.subject.other	engineering	en
dc.subject.other	Escherichia coli	en
dc.subject.other	feedback system	en
dc.subject.other	gene expression	en
dc.subject.other	human	en
dc.subject.other	human cell	en
dc.subject.other	prediction	en
dc.subject.other	quantitative analysis	en
dc.subject.other	signal transduction	en
dc.subject.other	systems biology	en
dc.subject.other	T lymphocyte	en
dc.subject.other	yeast	en
dc.title	Towards a rigorous assessment of systems biology models: The DREAM3 challenges	en
heal.type	journalArticle	en
heal.identifier.primary	10.1371/journal.pone.0009202	en
heal.identifier.secondary	http://dx.doi.org/10.1371/journal.pone.0009202	en
heal.identifier.secondary	e9202	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	Background: Systems biology has embraced computational modeling in response to the quantitative nature and increasing scale of contemporary data sets. The on-slaught of data is accelerating as molecular profiling technology evolves. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) is a community effort to catalyze discussion about the design, application, and assessment of systems biology models through annual reverse-engineering challenges. Methodology and Principal Findings: We describe our assessments of the four challenges associated with the third DREAM conference which came to be known as the DREAM3 challenges: signaling cascade identification, signaling response prediction, gene expression prediction, and the DREAM3 in silico network challenge. The challenges, based on anonymized data sets, tested participants in network inference and prediction of measurements. Forty teams submitted 413 predicted networks and measurement test sets. Overall, a handful of best-performer teams were identified, while a majority of teams made predictions that were equivalent to random. Counterintuitively, combining the predictions of multiple teams (including the weaker teams) can in some cases improve predictive power beyond that of any single method. Conclusions: DREAM provides valuable feedback to practitioners of systems biology modeling. Lessons learned from the predictions of the community provide much-needed context for interpreting claims of efficacy of algorithms described in the scientific literature. © 2010 Prill et al.	en
heal.publisher	PUBLIC LIBRARY SCIENCE	en
heal.journalName	PLoS ONE	en
dc.identifier.doi	10.1371/journal.pone.0009202	en
dc.identifier.isi	ISI:000274924000002	en
dc.identifier.volume	5	en
dc.identifier.issue	2	en