TRRUST: A reference database of human transcriptional regulatory interactions

Heonjong Han, Hongseok Shim, Donghyun Shin, Jung Eun Shim, Yunhee Ko, Junha Shin, Hanhae Kim, Ara Cho, Eiru Kim, Tak Lee, Hyojin Kim, Kyungsoo Kim, Sunmo Yang, Dasom Bae, Ayoung Yun, Sunphil Kim, Chan Yeong Kim, Hyeon Jin Cho, Byunghee Kang, Susie ShinInsuk Lee

Research output: Contribution to journalArticlepeer-review

255 Citations (Scopus)


The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining,, which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.

Original languageEnglish
Article number11432
JournalScientific reports
Publication statusPublished - 2015 Jun 12

Bibliographical note

Funding Information:
This work was supported by grants from the National Research Foundation of Korea (2012M3A9B4028641, 2012M3A9C7050151) to I.L.

All Science Journal Classification (ASJC) codes

  • General


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