{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T05:20:35Z","timestamp":1674710435881},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"17","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Due to recent advances in high-throughput technologies, data on various types of genomic annotation have accumulated. These data will be crucially helpful for elucidating the combinatorial logic of transcription. Although several approaches have been proposed for inferring cooperativity among multiple factors, most approaches are haunted by the issues of normalization and threshold values.<\/jats:p>\n               <jats:p>Results: In this article, we propose a rank-based non-parametric statistical test for measuring the effects between two gene sets. This method is free from the issues of normalization and threshold value determination for gene expression values. Furthermore, we have proposed an efficient Markov chain Monte Carlo method for calculating an approximate significance value of synergy. We have applied this approach for detecting synergistic combinations of transcription factor binding motifs and histone modifications.<\/jats:p>\n               <jats:p>Availability: C implementation of the method is available from http:\/\/www.hgc.jp\/~yshira\/software\/rankSynergy.zip.<\/jats:p>\n               <jats:p>Contact: \u00a0yshira@hgc.jp<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr382","type":"journal-article","created":{"date-parts":[[2011,6,24]],"date-time":"2011-06-24T01:56:40Z","timestamp":1308880600000},"page":"2399-2405","source":"Crossref","is-referenced-by-count":3,"title":["A rank-based statistical test for measuring synergistic effects between two gene sets"],"prefix":"10.1093","volume":"27","author":[{"given":"Yuichi","family":"Shiraishi","sequence":"first","affiliation":[{"name":"1 Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and 2Laboratory for Cellular Systems Modeling, RIKEN Research Center for Allergy and Immunology, Yokohama 230-0045, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mariko","family":"Okada-Hatakeyama","sequence":"additional","affiliation":[{"name":"1 Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and 2Laboratory for Cellular Systems Modeling, RIKEN Research Center for Allergy and Immunology, Yokohama 230-0045, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Satoru","family":"Miyano","sequence":"additional","affiliation":[{"name":"1 Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639 and 2Laboratory for Cellular Systems Modeling, RIKEN Research Center for Allergy and Immunology, Yokohama 230-0045, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2011,6,23]]},"reference":[{"key":"2023012511533527200_B1","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1038\/msb4100124","article-title":"Computational analysis of the synergy among multiple interacting genes","volume":"3","author":"Anastassiou","year":"2007","journal-title":"Mol. 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