{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T23:02:20Z","timestamp":1773270140042,"version":"3.50.1"},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2004,5,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: A number of models have been proposed for genetic regulatory networks. In principle, a network may contain any number of genes, so long as data are available to make inferences about their relationships. Nevertheless, there are two important reasons why the size of a constructed network should be limited. Computationally and mathematically, it is more feasible to model and simulate a network with a small number of genes. In addition, it is more likely that a small set of genes maintains a specific core regulatory mechanism.<\/jats:p>\n               <jats:p>Results: Subnetworks are constructed in the context of a directed graph by beginning with a seed consisting of one or more genes believed to participate in a viable subnetwork. Functionalities and regulatory relationships among seed genes may be partially known or they may simply be of interest. Given the seed, we iteratively adjoin new genes in a manner that enhances subnetwork autonomy. The algorithm is applied using both the coefficient of determination and the Boolean-function influence among genes, and it is illustrated using a glioma gene-expression dataset.<\/jats:p>\n               <jats:p>Availability: Software for the seed-growing algorithm will be available at the website for Probabilistic Boolean Networks: http:\/\/www2.mdanderson.org\/app\/ilya\/PBN\/PBN.htm<\/jats:p>","DOI":"10.1093\/bioinformatics\/bth074","type":"journal-article","created":{"date-parts":[[2004,3,2]],"date-time":"2004-03-02T21:41:06Z","timestamp":1078263666000},"page":"1241-1247","source":"Crossref","is-referenced-by-count":82,"title":["Growing genetic regulatory networks from seed genes"],"prefix":"10.1093","volume":"20","author":[{"given":"Ronaldo F.","family":"Hashimoto","sequence":"first","affiliation":[]},{"given":"Seungchan","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Ilya","family":"Shmulevich","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Michael L.","family":"Bittner","sequence":"additional","affiliation":[]},{"given":"Edward R.","family":"Dougherty","sequence":"additional","affiliation":[]}],"member":"286","published-online":{"date-parts":[[2004,2,10]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/20\/8\/1241\/48905472\/bioinformatics_20_8_1241.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/20\/8\/1241\/48905472\/bioinformatics_20_8_1241.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T17:29:37Z","timestamp":1674667777000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/20\/8\/1241\/209981"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,2,10]]},"references-count":0,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2004,5,22]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bth074","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2004,5,22]]},"published":{"date-parts":[[2004,2,10]]}}}