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It is however a notoriously difficult problem, for which the many existing methods reach limited accuracy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this paper, we formulate GRN inference as a sparse regression problem and investigate the performance of a popular feature selection method, least angle regression (LARS) combined with stability selection, for that purpose. We introduce a novel, robust and accurate scoring technique for stability selection, which improves the performance of feature selection with LARS. The resulting method, which we call TIGRESS (for Trustful Inference of Gene REgulation with Stability Selection), was ranked among the top GRN inference methods in the DREAM5 gene network inference challenge. In particular, TIGRESS was evaluated to be the best linear regression-based method in the challenge. We investigate in depth the influence of the various parameters of the method, and show that a fine parameter tuning can lead to significant improvements and state-of-the-art performance for GRN inference, in both directed and undirected settings.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>TIGRESS reaches state-of-the-art performance on benchmark data, including both<jats:italic>in silico<\/jats:italic>and<jats:italic>in vivo<\/jats:italic>(<jats:italic>E. coli<\/jats:italic>and<jats:italic>S. cerevisiae<\/jats:italic>) networks. This study confirms the potential of feature selection techniques for GRN inference. Code and data are available on<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/cbio.ensmp.fr\/tigress\" ext-link-type=\"uri\">http:\/\/cbio.ensmp.fr\/tigress<\/jats:ext-link>. Moreover, TIGRESS can be run online through the GenePattern platform (GP-DREAM,<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/dream.broadinstitute.org\" ext-link-type=\"uri\">http:\/\/dream.broadinstitute.org<\/jats:ext-link>).<\/jats:p><\/jats:sec>","DOI":"10.1186\/1752-0509-6-145","type":"journal-article","created":{"date-parts":[[2012,11,22]],"date-time":"2012-11-22T21:14:34Z","timestamp":1353618874000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":358,"title":["TIGRESS: Trustful Inference of Gene REgulation using Stability Selection"],"prefix":"10.1186","volume":"6","author":[{"given":"Anne-Claire","family":"Haury","sequence":"first","affiliation":[]},{"given":"Fantine","family":"Mordelet","sequence":"additional","affiliation":[]},{"given":"Paola","family":"Vera-Licona","sequence":"additional","affiliation":[]},{"given":"Jean-Philippe","family":"Vert","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,11,22]]},"reference":[{"issue":"5330","key":"1052_CR1","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1126\/science.277.5330.1275","volume":"277","author":"A Arkin","year":"1997","unstructured":"Arkin A, Shen P, Ross J: A test case of correlation metric construction of a reaction pathway from measurements. 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