Systematic selection of chemical fingerprint features improves the Gibbs energy prediction of biochemical reactions.

Journal: Bioinformatics (Oxford, England)
Published Date: Aug 1, 2019

Abstract

MOTIVATION: Accurate and wide-ranging prediction of thermodynamic parameters for biochemical reactions can facilitate deeper insights into the workings and the design of metabolic systems.

Authors

  • Meshari Alazmi
    King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Thuwal, Saudi Arabia.
  • Hiroyuki Kuwahara
    Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
  • Othman Soufan
    Institute of Parasitology, McGill University, Montreal, Quebec, Canada.
  • Lizhong Ding
    Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, UAE.
  • Xin Gao
    Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.

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