RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse
By Zhiping Liu, Canglin Wu, Hongyu Miao, Hulin Wu. Database J. Biol. Databases Curation, 2015
496 citations recorded by the source corpus.
Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/6787a08978444d97d6860359ba24b5a735d492e2
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In Molecular Biology
- Guangyan Zhou
- Robert E. W. Hancock
- Jessica Ewald
- Othman Soufan
- Niladri Basu
- Jianguo Xia
- J. Sáez-Rodríguez
- Luz Garcia-Alonso
Citations in the corpus
- Network-based machine learning and graph theory algorithms for precision oncology (2017, background): “16, 17 A transcriptional regulatory network is a directed graph in which the edges connect a regulator to its targets.”
- NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis (2019, methodology): “We also included the TF–miRNA–gene coregulatory networks built by RegNetwork (24).”
- Benchmark and integration of resources for the estimation of human transcription factor activities (2018, methodology): “TRED interactions were retrieved via the RegNetwork database (Liu et al. 2015).”