Dragon TF Association Miner: a system for exploring transcription factor associations through text-mining.
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/.
Pan
Hong
H
Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.
Zuo
Li
L
Choudhary
Vidhu
V
Zhang
Zhuo
Z
Leow
Shoi Houi
SH
Chong
Fui Teen
FT
Huang
Yingliang
Y
Ong
Victor Wui Siong
VW
Mohanty
Bijayalaxmi
B
Tan
Sin Lam
SL
Krishnan
S P T
SP
Bajic
Vladimir B
VB
D005786:Gene Expression Regulation; D020407:Internet; D039781:PubMed; D015398:Signal Transduction; D012984:Software; D014157:Transcription Factors / Q000378:metabolism* / Q000502:physiology; D014158:Transcription, Genetic; D014584:User-Computer Interface
D014157:Transcription Factors