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Although many factors affecting biofilm have been analyzed, molecular mechanisms that regulate biofilm formation still await to be elucidated.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In this study, from the gene regulatory network perspective, we developed an efficient computational framework, which integrates different kinds of data from genome-scale analysis, for global screening of potential transcription factors (TFs) controlling <jats:italic>C. albicans<\/jats:italic> biofilm formation. <jats:italic>S. cerevisiae<\/jats:italic> information and ortholog data were used to infer the possible TF-gene regulatory associations in <jats:italic>C. albicans<\/jats:italic>. Based on TF-gene regulatory associations and gene expression profiles, a stochastic dynamic model was employed to reconstruct the gene regulatory networks of <jats:italic>C. albicans<\/jats:italic> biofilm and planktonic cells. The two networks were then compared and a score of relevance value (RV) was proposed to determine and assign the quantity of correlation of each potential TF with biofilm formation. A total of twenty-three TFs are identified to be related to the biofilm formation; ten of them are previously reported by literature evidences.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>The results indicate that the proposed screening method can successfully identify most known biofilm-related TFs and also identify many others that have not been previously reported. Together, this method can be employed as a pre-experiment screening approach that reveals new target genes for further characterization to understand the regulatory mechanisms in biofilm formation, which can serve as the starting point for therapeutic intervention of <jats:italic>C. albicans<\/jats:italic> infections.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-11-53","type":"journal-article","created":{"date-parts":[[2010,1,26]],"date-time":"2010-01-26T19:15:40Z","timestamp":1264533340000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Global screening of potential Candida albicans biofilm-related transcription factors via network comparison"],"prefix":"10.1186","volume":"11","author":[{"given":"Yu-Chao","family":"Wang","sequence":"first","affiliation":[]},{"given":"Chung-Yu","family":"Lan","sequence":"additional","affiliation":[]},{"given":"Wen-Ping","family":"Hsieh","sequence":"additional","affiliation":[]},{"given":"Luis A","family":"Murillo","sequence":"additional","affiliation":[]},{"given":"Nina","family":"Agabian","sequence":"additional","affiliation":[]},{"given":"Bor-Sen","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,1,26]]},"reference":[{"key":"3510_CR1","doi-asserted-by":"publisher","first-page":"e39","DOI":"10.1371\/journal.pgen.0010039","volume":"1","author":"J Ihmels","year":"2005","unstructured":"Ihmels J, Bergmann S, Berman J, Barkai N: Comparative gene expression analysis by differential clustering approach: application to the Candida albicans transcription program. 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