| Literature DB >> 29087512 |
Heonjong Han1, Jae-Won Cho1, Sangyoung Lee1, Ayoung Yun1, Hyojin Kim1, Dasom Bae1, Sunmo Yang1, Chan Yeong Kim1, Muyoung Lee1, Eunbeen Kim1, Sungho Lee1, Byunghee Kang1, Dabin Jeong1, Yaeji Kim1, Hyeon-Nae Jeon1, Haein Jung1, Sunhwee Nam1, Michael Chung1, Jong-Hoon Kim2, Insuk Lee1.
Abstract
Transcription factors (TFs) are major trans-acting factors in transcriptional regulation. Therefore, elucidating TF-target interactions is a key step toward understanding the regulatory circuitry underlying complex traits such as human diseases. We previously published a reference TF-target interaction database for humans-TRRUST (Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining)-which was constructed using sentence-based text mining, followed by manual curation. Here, we present TRRUST v2 (www.grnpedia.org/trrust) with a significant improvement from the previous version, including a significantly increased size of the database consisting of 8444 regulatory interactions for 800 TFs in humans. More importantly, TRRUST v2 also contains a database for TF-target interactions in mice, including 6552 TF-target interactions for 828 mouse TFs. TRRUST v2 is also substantially more comprehensive and less biased than other TF-target interaction databases. We also improved the web interface, which now enables prioritization of key TFs for a physiological condition depicted by a set of user-input transcriptional responsive genes. With the significant expansion in the database size and inclusion of the new web tool for TF prioritization, we believe that TRRUST v2 will be a versatile database for the study of the transcriptional regulation involved in human diseases.Entities:
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Year: 2018 PMID: 29087512 PMCID: PMC5753191 DOI: 10.1093/nar/gkx1013
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971