Acceleration of PDE-Based Biological Simulation Through the Development of Neural Network Metamodels.

Journal: Current pathobiology reports
Published Date: Nov 6, 2020

Abstract

PURPOSE OF REVIEW: Partial differential equation (PDE) mathematical models of biological systems and the simulation approaches used to solve them are widely used to test hypotheses and infer regulatory interactions based on optimization of the PDE model against the observed data. In this review, we discuss the ability of powerful machine learning methods to accelerate the parametric screening of biophysical informed- PDE systems.

Authors

  • Lukasz Burzawa
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.
  • Linlin Li
    Department of Clinical Pharmacy, School of Pharmacy, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong, 271016, China.
  • Xu Wang
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.
  • Adrian Buganza-Tepole
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.
  • David M Umulis
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.

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