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.
Bibliographical noteFunding Information:
National Research Foundation of Korea [2015R1A2A1A1 5055859, 2017M3A9B4042581]; Brain Korea 21 (BK21) PLUS program (to I.L.). Funding for open access charge: National Research Foundation of Korea. Conflict of interest statement. None declared.
National Research Foundation of Korea [2015R1A2A1A1 5055859, 2017M3A9B4042581]; Brain Korea 21 (BK21) PLUS program (to I.L.).
© 2017 The Author(s).
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