{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T09:26:52Z","timestamp":1687858012064},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"15","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive \u2018noise\u2019 in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context.<\/jats:p>\n               <jats:p>Results: In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer.<\/jats:p>\n               <jats:p>Availability and implementation: The Gibbs sampler MATLAB package is freely available at http:\/\/www.cbil.ece.vt.edu\/software.htm.<\/jats:p>\n               <jats:p>Contact: \u00a0xuan@vt.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts296","type":"journal-article","created":{"date-parts":[[2012,5,18]],"date-time":"2012-05-18T01:07:57Z","timestamp":1337303277000},"page":"1990-1997","source":"Crossref","is-referenced-by-count":8,"title":["Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic"],"prefix":"10.1093","volume":"28","author":[{"given":"Jinghua","family":"Gu","sequence":"first","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhua","family":"Xuan","sequence":"additional","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rebecca B.","family":"Riggins","sequence":"additional","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Chen","sequence":"additional","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Wang","sequence":"additional","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Clarke","sequence":"additional","affiliation":[{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"},{"name":"1 Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA 22203, 2Lombardi Comprehensive Cancer Center and Department of Oncology and 3Department of Physiology and Biophysics, Georgetown University, Washington, DC 20057, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,5,17]]},"reference":[{"key":"2023012512452529300_B1","doi-asserted-by":"crossref","first-page":"6071","DOI":"10.1038\/onc.2010.333","article-title":"Biological reprogramming in acquired resistance to endocrine therapy of breast cancer","volume":"29","author":"Aguilar","year":"2010","journal-title":"Oncogene"},{"key":"2023012512452529300_B2","doi-asserted-by":"crossref","first-page":"10101","DOI":"10.1073\/pnas.97.18.10101","article-title":"Singular value decomposition for genome-wide expression data processing and modeling","volume":"97","author":"Alter","year":"2000","journal-title":"Proc. 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