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Since 2019, Matheon's application-oriented mathematical research activities are being continued in the framework of the Cluster of Excellence MATH+
www.mathplus.de
The Matheon websites will not be updated anymore.

Dr. Wei Zhang

wei.zhang@fu-berlin.de


Projekte als Mitglied

  • CH21

    Data-Driven Modelling of Cellular Processes and beyond

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

    Projektleiter: Prof. Dr. Tim Conrad / Dr. Stefan Klus / Prof. Dr. Christof Schütte
    Projekt Mitglieder: Dr. Wei Zhang
    Laufzeit: 01.06.2017 - 31.12.2019
    Status: laufend
    Standort: Konrad-Zuse-Zentrum für Informationstechnik Berlin

    Beschreibung

    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.

    http://medicalbioinformatics.de/research/projects/ecmath-ch21
  • CH4

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

    Dr. Max von Kleist / PD Dr. Marcus Weber

    Projektleiter: Dr. Max von Kleist / PD Dr. Marcus Weber
    Projekt Mitglieder: Dr. Wei Zhang
    Laufzeit: -
    Status: beendet
    Standort: Freie Universität Berlin

    Beschreibung

    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

Projekte als Gast