A computational procedure for identifying master regulator candidates: a case study on diabetes progression in Goto-Kakizaki rats
文献类型：期刊论文
| 作者 | Piao,Guanying1,2; Saito,Shigeru3,4; Sun,Yidan2,5; Liu,Zhi-Ping2,6; Wang,Yong6 ; Han,Xiao5; Wu,Jiarui1,2; Zhou,Huarong2; Chen,Luonan2,3; Horimoto,Katsuhisa3
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| 刊名 | BMC Systems Biology
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| 出版日期 | 2012-07-16 |
| 卷号 | 6期号:Suppl 1 |
| ISSN号 | 1752-0509 |
| DOI | 10.1186/1752-0509-6-S1-S2 |
| 英文摘要 | AbstractBackgroundWe have recently identified a number of active regulatory networks involved in diabetes progression in Goto-Kakizaki (GK) rats by network screening. The networks were quite consistent with the previous knowledge of the regulatory relationships between transcription factors (TFs) and their regulated genes. To study the underlying molecular mechanisms directly related to phenotype changes, such as diseases, we also previously developed a computational procedure for identifying transcriptional master regulators (MRs) in conjunction with network screening and network inference, by effectively perturbing the phenotype states.ResultsIn this work, we further improved our previous method for identifying MR candidates, by listing them in a more reliable manner, and applied the method to reveal the MR candidates for diabetes progression in GK rats from the active networks. Specifically, the active TF-gene pairs for different time periods in GK rats were first extracted from the networks by network screening. Another set of active TF-gene pairs was selected by network inference, by considering the gene expression signatures for those periods between GK and Wistar-Kyoto (WKY) rats. The TF-gene pairs extracted by the two methods were then further selected, from the viewpoints of the emergence specificity of TF in GK rats and the regulated-gene coverage of TF in the expression signature. Finally, we narrowed all of the genes down to only 5 TFs (Etv4, Fus, Nr2f1, Sp2, and Tcfap2b) as the candidates of MRs, with 54 regulated genes, by merging the selected TF-gene pairs.ConclusionsThe present method has successfully identified biologically plausible MR candidates, including the TFs related to diabetes in previous reports. Although the experimental verifications of the candidates and the present procedure are beyond the scope of this study, we narrowed down the candidates to 5 TFs, which can be used to perform the verification experiments relatively easily. The numerical results showed that our computational method is an efficient way to detect the key molecules responsible for biological phenomena. |
| 语种 | 英语 |
| WOS记录号 | BMC:10.1186/1752-0509-6-S1-S2 |
| 出版者 | BioMed Central |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/257]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | Wu,Jiarui; Zhou,Huarong; Chen,Luonan; Horimoto,Katsuhisa |
| 作者单位 | 1.University of Science and Technology of China; School of Life Sciences 2.Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences; Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes 3.National Institute of Advanced Industrial Science and Technology; Computational Biology Research Center 4.INFOCOM Corporation 5.Nanjing Medical University; Key Laboratory of Human Functional Genomics of Jiangsu Province 6.Academy of Mathematics and Systems Science, Chinese Academy of Sciences; National Center for Mathematics and Interdisciplinary Sciences |
| 推荐引用方式 GB/T 7714 | Piao,Guanying,Saito,Shigeru,Sun,Yidan,et al. A computational procedure for identifying master regulator candidates: a case study on diabetes progression in Goto-Kakizaki rats[J]. BMC Systems Biology,2012,6(Suppl 1). |
| APA | Piao,Guanying.,Saito,Shigeru.,Sun,Yidan.,Liu,Zhi-Ping.,Wang,Yong.,...&Horimoto,Katsuhisa.(2012).A computational procedure for identifying master regulator candidates: a case study on diabetes progression in Goto-Kakizaki rats.BMC Systems Biology,6(Suppl 1). |
| MLA | Piao,Guanying,et al."A computational procedure for identifying master regulator candidates: a case study on diabetes progression in Goto-Kakizaki rats".BMC Systems Biology 6.Suppl 1(2012). |
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来源：数学与系统科学研究院
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