4.7 Article

Bio2Rxn: sequence-based enzymatic reaction predictions by a consensus strategy

Journal

BIOINFORMATICS
Volume 36, Issue 11, Pages 3600-3601

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa135

Keywords

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Funding

  1. National Key Research and Development Program of China [2019YFA0904300, 2018YFA0900700, 2017YFC1601702]
  2. National Natural Science Foundation of China [31700081, 31570092]
  3. Scientific Research Conditions and Technical Support System Program [ZSYS-016]
  4. Science and Technology Service Network Initiative (STS) program of the Chinese Academy of Sciences of China [QYZDB-SSW-SMC012]
  5. International Partnership Program of Chinese Academy of Sciences of China [153D31KYSB20170121]
  6. Natural Science Foundation of Tianjin [15JCYBJC54300]

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The development of sequencing technologies has generated large amounts of protein sequence data. The automated prediction of the enzymatic reactions of uncharacterized proteins is a major challenge in the field of bioinformatics. Here, we present Bio2Rxn as a web-based tool to provide putative enzymatic reaction predictions for uncharacterized protein sequences. Bio2Rxn adopts a consensus strategy by incorporating six types of enzyme prediction tools. It allows for the efficient integration of these computational resources to maximize the accuracy and comprehensiveness of enzymatic reaction predictions, which facilitates the characterization of the functional roles of target proteins in metabolism. Bio2Rxn further links the enzyme function prediction with more than 300 000 enzymatic reactions, which were manually curated by more than 100 people over the past 9 years from more than 580 000 publications.

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