Modeling biological systems with uncertain kinetic data using fuzzy continuous Petri nets.

Journal: BMC systems biology
Published Date: Apr 24, 2018

Abstract

BACKGROUND: Uncertainties exist in many biological systems, which can be classified as random uncertainties and fuzzy uncertainties. The former can usually be dealt with using stochastic methods, while the latter have to be handled with such approaches as fuzzy methods.

Authors

  • Fei Liu
    Department of Interventional Radiology, Qinghai Red Cross Hospital, Xining, Qinghai, China.
  • Siyuan Chen
    First author: Department of Computer Science, Columbia University in the City of New York, 10027; second, fourth, and sixth authors: Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853; third author: Department of Mechanical Engineering, Columbia University; fifth author: Uber AI Labs, San Francisco 94103; seventh author: Plant Pathology and Plant-Microbe Biology Section, School of Integrative Plant Science, Cornell University; and eighth author: Department of Mechanical Engineering and Institute of Data Science, Columbia University.
  • Monika Heiner
    Computer Science Institute, Brandenburg University of Technology, Cottbus, 10 13 44, Germany.
  • Hengjie Song
    School of Software Engineering, South China University of Technology, Guangzhou 510006, China.

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