Article: EpiRegNet: Constructing epigenetic regulatory network from high throughput gene expression data for humans
| Title | EpiRegNet: Constructing epigenetic regulatory network from high throughput gene expression data for humans |
|---|---|
| Authors | Wang, LY1 Wang, P1 Li, MJ1 Qin, J1 Wang, X3 Zhang, MQ2 3 Wang, J1 |
| Issue Date | 2011 |
| Publisher | Landes Bioscience. The Journal's web site is located at http://www.landesbioscience.com/journals/epigenetics |
| Citation | Epigenetics, 2011, v. 6 n. 12, p. 1505-1512 [How to Cite?] DOI: http://dx.doi.org/10.4161/epi.6.12.18176 |
| Abstract | The advances of high throughput profiling methods, such as microarray gene profiling and RNA-seq, have enabled researchers to identify thousands of differentially expressed genes under a certain perturbation. Much work has been done to understand the genetic factors that contribute to the expression changes by searching the overrepresented regulatory motifs in the promoter regions of these genes. However, the changes could also be caused by epigenetic regulation, especially histone modifications, and no web server has been constructed to study the epigenetic factors responsible for gene expression changes. Here, we present a web tool for this purpose. Provided with different categories of genes (e.g., upregulated, downregulated or unchanged genes), the server will find epigenetic factors responsible for the difference among the categories and construct an epigenetic regulatory network. Furthermore, it will perform colocalization analyses between these epigenetic factors and transcription factors, which were collected from large scale experimental ChIP-seq or computational predicted data. In addition, for users who want to analyze dynamic change of a histone modification mark under different cell conditions, the server will find direct and indirect target genes of this mark by integrative analysis of experimental data and computational prediction, and present a regulatory network around this mark. Both networks can be visualized by a user friendly interface and the data are downloadable in batch. The server currently supports 12 cell types in human, including ESC and CD4 + T cells, and will expand as more public data are available. It also allows user to create a self-defined cell type, upload and analyze multiple ChIP-seq data. It is freely available to academic users at http://jjwanglab.org/EpiRegNet. © 2011 Landes Bioscience. |
| ISSN | 1559-2294 2011 Impact Factor: 4.318 2011 SCImago Journal Rankings: 0.518 |
| DOI | http://dx.doi.org/10.4161/epi.6.12.18176 |
| References | References in Scopus |
| Grants | A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus |
| dc.contributor.author | Wang, LY | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| dc.contributor.author | Wang, P | ||||||||
| dc.contributor.author | Li, MJ | ||||||||
| dc.contributor.author | Qin, J | ||||||||
| dc.contributor.author | Wang, X | ||||||||
| dc.contributor.author | Zhang, MQ | ||||||||
| dc.contributor.author | Wang, J | ||||||||
| dc.date.accessioned | 2012-05-29T06:05:17Z | ||||||||
| dc.date.available | 2012-05-29T06:05:17Z | ||||||||
| dc.date.issued | 2011 | ||||||||
| dc.description.abstract | The advances of high throughput profiling methods, such as microarray gene profiling and RNA-seq, have enabled researchers to identify thousands of differentially expressed genes under a certain perturbation. Much work has been done to understand the genetic factors that contribute to the expression changes by searching the overrepresented regulatory motifs in the promoter regions of these genes. However, the changes could also be caused by epigenetic regulation, especially histone modifications, and no web server has been constructed to study the epigenetic factors responsible for gene expression changes. Here, we present a web tool for this purpose. Provided with different categories of genes (e.g., upregulated, downregulated or unchanged genes), the server will find epigenetic factors responsible for the difference among the categories and construct an epigenetic regulatory network. Furthermore, it will perform colocalization analyses between these epigenetic factors and transcription factors, which were collected from large scale experimental ChIP-seq or computational predicted data. In addition, for users who want to analyze dynamic change of a histone modification mark under different cell conditions, the server will find direct and indirect target genes of this mark by integrative analysis of experimental data and computational prediction, and present a regulatory network around this mark. Both networks can be visualized by a user friendly interface and the data are downloadable in batch. The server currently supports 12 cell types in human, including ESC and CD4 + T cells, and will expand as more public data are available. It also allows user to create a self-defined cell type, upload and analyze multiple ChIP-seq data. It is freely available to academic users at http://jjwanglab.org/EpiRegNet. © 2011 Landes Bioscience. | ||||||||
| dc.description.grant | A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus | ||||||||
| dc.description.grantcode | 103716 | ||||||||
| dc.description.nature | Link_to_OA_fulltext | ||||||||
| dc.identifier.citation | Epigenetics, 2011, v. 6 n. 12, p. 1505-1512 [How to Cite?] DOI: http://dx.doi.org/10.4161/epi.6.12.18176 | ||||||||
| dc.identifier.citeulike | 11175267 | ||||||||
| dc.identifier.doi | http://dx.doi.org/10.4161/epi.6.12.18176 | ||||||||
| dc.identifier.epage | 1512 | ||||||||
| dc.identifier.hkuros | 208294 | ||||||||
| dc.identifier.isi | WOS:000299828200012
Funding Information: We thank Sam Bevan for editing the manuscript. The project was supported by University Postgraduate Fellowships (to L.Y.W. and J.Q.) from the University of Hong Kong, the Research Grants Council of Hong Kong (N_HKU752/10, 781511M, 778609M, AoE M04/04), and Food and Health Bureau of Hong Kong (10091262). | ||||||||
| dc.identifier.issn | 1559-2294 2011 Impact Factor: 4.318 2011 SCImago Journal Rankings: 0.518 | ||||||||
| dc.identifier.issue | 12 | ||||||||
| dc.identifier.pmid | 22139581 | ||||||||
| dc.identifier.scopus | eid_2-s2.0-83255166557 | ||||||||
| dc.identifier.spage | 1505 | ||||||||
| dc.identifier.uri | http://hdl.handle.net/10722/147656 | ||||||||
| dc.identifier.volume | 6 | ||||||||
| dc.language | eng | ||||||||
| dc.publisher | Landes Bioscience. The Journal's web site is located at http://www.landesbioscience.com/journals/epigenetics | ||||||||
| dc.publisher.place | United States | ||||||||
| dc.relation.ispartof | Epigenetics | ||||||||
| dc.relation.references | References in Scopus | ||||||||
| dc.subject.mesh | Databases, Genetic | ||||||||
| dc.subject.mesh | Epigenesis, Genetic | ||||||||
| dc.subject.mesh | Gene Regulatory Networks - Genetics | ||||||||
| dc.subject.mesh | Histones - Metabolism | ||||||||
| dc.subject.mesh | Humans | ||||||||
| dc.subject.mesh | Internet | ||||||||
| dc.subject.mesh | Software | ||||||||
| dc.title | EpiRegNet: Constructing epigenetic regulatory network from high throughput gene expression data for humans | ||||||||
| dc.type | Article |
Author Affiliations
- The University of Hong Kong Li Ka Shing Faculty of Medicine
- University of Texas at Dallas
- Tsinghua University