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Nucleic Acids Research 2004 32(Web Server Issue):W230-W234; doi:10.1093/nar/gkh484
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© 2004, the authors
Nucleic Acids Research, Vol. 32, Web Server issue © Oxford University Press 2004; all rights reserved

Dragon TF Association Miner: a system for exploring transcription factor associations through text-mining

Hong Pan, Li Zuo, Vidhu Choudhary, Zhuo Zhang, Shoi Houi Leow, Fui Teen Chong, Yingliang Huang, Victor Wui Siong Ong, Bijayalaxmi Mohanty, Sin Lam Tan, S. P. T. Krishnan and Vladimir B. Bajic*

Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613

* To whom correspondence should be addressed. Tel: +65 6874 8800; Fax: +65 6774 8056; Email: bajicv{at}i2r.a-star.edu.sg

Received February 15, 2004; Revised April 19, 2004; Accepted May 5, 2004

We present Dragon TF Association Miner (DTFAM), a system for text-mining of PubMed documents for potential functional association of transcription factors (TFs) with terms from Gene Ontology (GO) and with diseases. DTFAM has been trained and tested in the selection of relevant documents on a manually curated dataset containing >3000 PubMed abstracts relevant to transcription control. On our test data the system achieves sensitivity of 80% with specificity of 82%. DTFAM provides comprehensive tabular and graphical reports linking terms to relevant sets of documents. These documents are color-coded for easier inspection. DTFAM complements the existing biological resources by collecting, assessing, extracting and presenting associations that can reveal some of the not so easily observable connections among the entities found which could explain the functions of TFs and help decipher parts of gene transcriptional regulatory networks. DTFAM summarizes information from a large volume of documents saving time and making analysis simpler for individual users. DTFAM is freely available for academic and non-profit users at http://research.i2r.a-star.edu.sg/DRAGON/TFAM/.

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