GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Biological data has grown explosively with the advance of next-generation sequencing. However, annotating protein function with wet lab experiments is time-consuming. Fortunately, computational function prediction can help wet labs formulate biological hypotheses and prioritize experiments. Gene Ontology (GO) is a framework for unifying the representation of protein function in a hierarchical tree composed of GO terms.

Authors

  • Yi-Wei Liu
    Department of Computer Science, National Chengchi University, 11605, Taipei, Taiwan.
  • Tz-Wei Hsu
    Department of Computer Science, National Chengchi University, 11605, Taipei, Taiwan.
  • Che-Yu Chang
    Department of Computer Science, National Chengchi University, 11605, Taipei, Taiwan.
  • Wen-Hung Liao
    Department of Computer Science, National Chengchi University, 11605, Taipei, Taiwan. whliao@gmail.com.
  • Jia-Ming Chang
    Department of Computer Science, National Chengchi University, 11605, Taipei City, Taiwan. chang.jiaming@gmail.com.