Predicting Metabolic Reaction Networks with Perturbation-Theory Machine Learning (PTML) Models.

Journal: Current topics in medicinal chemistry
Published Date: Jan 1, 2021

Abstract

BACKGROUND: Checking the connectivity (structure) of complex Metabolic Reaction Networks (MRNs) models proposed for new microorganisms with promising properties is an important goal for chemical biology.

Authors

  • Karel Diéguez-Santana
    Department of Organic and Inorganic Chemistry, University of the Basque Country UPV/EHU, and Basque Center for Biophysics CSIC-UPV/EHU, Leioa 48940, Great Bilbao, Biscay, Basque Country, Spain.
  • Gerardo M Casañola-Martin
    Department of Systems and Computer Engineering, Carleton University, K1S 5B6, Ottawa, ON, Canada.
  • James R Green
    Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada. jrgreen@sce.carleton.ca.
  • Bakhtiyor Rasulev
    c Department of Coatings and Polymeric Materials , North Dakota State University , Fargo , ND , USA.
  • Humberto Gonzalez-Diaz

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