TACT: Transcriptome Auto-annotation Conducting Tool of H-InvDB

Chisato Yamasaki, Hiroaki Kawashima, Fusano Todokoro, Yasuhiro Imamizu, Makoto Ogawa, Motohiko Tanino, Takeshi Itoh, Takashi Gojobori, Tadashi Imanishi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Transcriptome Auto-annotation Conducting Tool (TACT) is a newly developed web-based automated tool for conducting functional annotation of transcripts by the integration of sequence similarity searches and functional motif predictions. We developed the TACT system by integrating two kinds of similarity searches, FASTY and BLASTX, against protein sequence databases, UniProtKB (Swiss-Prot/TrEMBL) and RefSeq, and a unified motif prediction program, InterProScan, into the ORF-prediction pipeline originally designed for the 'H-Invitational' human transcriptome annotation project. This system successively applies these constituent programs to an mRNA sequence in order to predict the most plausible ORF and the function of the protein encoded. In this study, we applied the TACT system to 19 574 non-redundant human transcripts registered in H-InvDB and evaluated its predictive power by the degree of agreement with human-curated functional annotation in H-InvDB. As a result, the TACT system could assign functional description to 12 559 transcripts (64.2%), the remainder being hypothetical proteins. Furthermore, the overall agreement of functional annotation with H-InvDB, including those transcripts annotated as hypothetical proteins, was 83.9% (16 432/19 574). These results show that the TACT system is useful for functional annotation and that the prediction of ORFs and protein functions is highly accurate and close to the results of human curation. TACT is freely available at http://www.jbirc.aist.go.jp/tact/.

Original languageEnglish (US)
Pages (from-to)W345-W349
Issue numberWEB. SERV. ISS.
StatePublished - Jul 2006
Externally publishedYes

Bibliographical note

Funding Information:
The authors thank Mr Ryo Aono for graphical design of the interfaces and Mr Tomohiro Endo for the technical support. The authors acknowledge all the members of the H-Invitational consortium, especially the staffs of JBIRC and DDBJ for construction of H-InvDB. This research is financially supported by the Ministry of Economy, Trade and Industry of Japan (METI), the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) and the Japan Biological Informatics Consortium (JBIC). Funding to pay the Open Access publication charges for this article was provided by JBIC.

ASJC Scopus subject areas

  • Genetics


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