000126163 001__ 126163
000126163 005__ 20190316234327.0
000126163 0247_ $$2doi$$a10.1111/j.1749-6632.2008.03945.x
000126163 02470 $$2ISI$$a000265650800010
000126163 037__ $$aARTICLE
000126163 245__ $$aCombining Multiple Results of a Reverse Engineering Algorithm: Application to the DREAM Five Gene Network Challenge
000126163 269__ $$a2009
000126163 260__ $$bBlackwell Publishing, 9600 Garsington Rd, Oxford Ox4 2Dq, Oxen, England$$c2009
000126163 336__ $$aJournal Articles
000126163 490__ $$aAnnals Of The New York Academy Of Sciences
000126163 520__ $$aThe output of reverse engineering methods for biological networks is often not a single network prediction, but an ensemble of networks that are consistent with the experimentally measured data. In this paper, we consider the problem of combining the information contained within such an ensemble in order to (1) make more accurate network predictions and (2) estimate the reliability of these predictions. We review existing methods, discuss their limitations, and point out possible research directions towards more advanced methods for this purpose. The potential of considering ensembles of networks, rather than individual inferred networks, is demonstrated by showing how an ensemble voting method achieved winning performance on the Five Gene Network Challenge of the second DREAM conference (Dialogue on Reverse Engineering Assessment and Methods 2007, New York, NY).
000126163 6531_ $$aEnsemble Methods
000126163 6531_ $$aDREAM Challenge
000126163 6531_ $$aGene Regulatory Networks
000126163 6531_ $$aReverse Engineering
000126163 6531_ $$aEvolutionary Robotics
000126163 700__ $$aMarbach, Daniel
000126163 700__ $$0241582$$aMattiussi, Claudio$$g140974
000126163 700__ $$0240742$$aFloreano, Dario$$g111729
000126163 773__ $$j1158$$q102-113$$tAnnals of the New York Academy of Sciences
000126163 8564_ $$s455780$$uhttps://infoscience.epfl.ch/record/126163/files/Marbach%202009%20Ann%20NY%20Acad%20Sci.pdf$$zn/a
000126163 909C0 $$0252161$$pLIS$$xU10370
000126163 909CO $$ooai:infoscience.tind.io:126163$$pSTI$$particle$$qGLOBAL_SET
000126163 917Z8 $$x255330
000126163 937__ $$aLIS-ARTICLE-2008-014
000126163 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000126163 980__ $$aARTICLE