Wei Zhang

wei.zhang@fu-berlin.de


Projects as a member

  • CH21

    Data-Driven Modelling of Cellular Processes and beyond

    Prof. Dr. Tim Conrad / Dr. Stefan Klus / Prof. Dr. Christof Schütte

    Project heads: Prof. Dr. Tim Conrad / Dr. Stefan Klus / Prof. Dr. Christof Schütte
    Project members: Wei Zhang
    Duration: 01.06.2017 - 31.12.2018
    Status: running
    Located at: Konrad-Zuse-Zentrum für Informationstechnik Berlin

    Description

    Cellular processes are governed by diffusion, transport, and interactions of its constituents. For many processes the spatial inhomogeneity of cells is of secondary importance; modelling such processes means finding appropriate kinetic models of the underlying cellular reaction networks (CRNs). The availability of such models is key to many areas of the life sciences ranging from computational biology to system medicine and is essential for understanding the fundamentals of cellular behavior, its malfunction under external stress and its restoration by regenerative interventions.

  • CH4

    Optimal control of chemical reaction systems and application to drug resistance mitigating therapy

    Prof. Dr. Carsten Hartmann / Dr. Max von Kleist / PD Dr. Marcus Weber

    Project heads: Prof. Dr. Carsten Hartmann / Dr. Max von Kleist / PD Dr. Marcus Weber
    Project members: Wei Zhang
    Duration: -
    Status: completed
    Located at: Freie Universität Berlin

    Description

    Development and spread of drug resistant microorganisms is a major health issue which, accompanied by an attrition in drug development, is expected to worsen in the near future. The source of drug resistance development is the inadequate use of antimicrobials: Inadequate therapies insufficiently suppress susceptible strains, which may give rise to a drug resistant type. At the same time, inadequate therapy exerts enough selective pressure to provide the newly emerged resistant strain with a selective advantage that allows it to become fixed in the population. In recent years, we have elaborated the idea, that an optimal switching between existing antimicrobial drugs may mitigate drug resistance development in the individual. Drug resistance development is an intrinsically stochastic process. This process can be accurately described by the chemical master equation (CME). A major mathematical drawback is the fact that the CME cannot be solved directly due to its numerical complexity. Therefore, computation of an optimal control/therapy based on a direct numerical solution of the CME is usually not feasible. The aim of the proposed project is to mathematically characterize and develop optimal control policies derived from approximations of the CME, and to use the developed methods to suggest drug mitigating therapies to clinical partners in the field of HIV-1 and antibiotic resistance.

    http://systems-pharmacology.de/?page_id=621

Projects as a guest