{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T18:28:40Z","timestamp":1687631320604},"reference-count":40,"publisher":"Walter de Gruyter GmbH","issue":"2","license":[{"start":{"date-parts":[[2017,7,4]],"date-time":"2017-07-04T00:00:00Z","timestamp":1499126400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,7,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Gene-regulatory networks are an abstract way of capturing the regulatory connectivity between transcription factors, microRNAs, and target genes in biological cells. Here, we address the problem of identifying enriched co-regulatory three-node motifs that are found significantly more often in real network than in randomized networks. First, we compare two randomization strategies, that either only conserve the degree distribution of the nodes\u2019 in- and out-links, or that also conserve the degree distributions of different regulatory edge types. Then, we address the issue how convergence of randomization can be measured. We show that after at most 10\u2009\u00d7\u2009|E| edge swappings, converged motif counts are obtained and the memory of initial edge identities is lost.<\/jats:p>","DOI":"10.1515\/jib-2017-0017","type":"journal-article","created":{"date-parts":[[2017,7,4]],"date-time":"2017-07-04T09:30:56Z","timestamp":1499160656000},"source":"Crossref","is-referenced-by-count":1,"title":["Randomization Strategies Affect Motif Significance Analysis in TF-miRNA-Gene Regulatory Networks"],"prefix":"10.1515","volume":"14","author":[{"given":"Sepideh","family":"Sadegh","sequence":"first","affiliation":[{"name":"Center for Bioinformatics, Saarland University, Saarbruecken, Germany"}]},{"given":"Maryam","family":"Nazarieh","sequence":"additional","affiliation":[{"name":"Center for Bioinformatics, Saarland University, Saarbruecken, Germany"},{"name":"Graduate School of Computer Science, Saarland University, Saarbruecken, Germany"}]},{"given":"Christian","family":"Spaniol","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Psychotherapy, Saarland University Hospital, Homburg, Germany"}]},{"given":"Volkhard","family":"Helms","sequence":"additional","affiliation":[{"name":"Center for Bioinformatics, Saarland University, Saarbruecken, Germany"}]}],"member":"374","reference":[{"key":"ref151","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1126\/science.298.5594.824","article-title":"Network motifs: simple building blocks of complex networks","volume":"298","year":"2002","journal-title":"Science"},{"key":"ref191","first-page":"44","article-title":"Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources","volume":"4","year":"2008","journal-title":"Nat Protoc"},{"key":"ref371","doi-asserted-by":"crossref","first-page":"2348","DOI":"10.1093\/bioinformatics\/btv159","article-title":"A novel motif-discovery algorithm to identify 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