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BioMed Research International
Volume 2015, Article ID 254838, 7 pages
Research Article

METSP: A Maximum-Entropy Classifier Based Text Mining Tool for Transporter-Substrate Identification with Semistructured Text

1School of Engineering, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Maroochydore DC, QLD 4558, Australia
2School of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China
3Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing 100871, China

Received 13 March 2015; Accepted 21 June 2015

Academic Editor: Shigehiko Kanaya

Copyright © 2015 Min Zhao et al. This is an open access paper distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

In Additional file 1, the 6955 TSPs were manually collected from UniProt, TransportDB, and TCDB. In Additional file 2, the training set includes 41,332 instances in the format of “label + accession number + field flag + a sentence.” In Additional file 3, the 3942 human TSPs were extracted by METSP.

  1. Supplementary Materials