Mustafa Hani Khammash: Katalogdaten im Frühjahrssemester 2020

NameHerr Prof. Dr. Mustafa Hani Khammash
LehrgebietRegelungstheorie und Systembiologie
Regelungstheorie u. Systembiologie
ETH Zürich, BSA M 700
Mattenstr. 26
4058 Basel
Auszeichnung: Die Goldene Eule
Telefon+41 61 387 33 56
BeziehungOrdentlicher Professor

636-0016-00LComputational Systems Biology: Stochastic Approaches Information 4 KP3GM. H. Khammash, A. Gupta
KurzbeschreibungThis course is concerned with the development of computational methods for modeling, simulation, and analysis of stochasticity in living cells. Using these tools, the course explores the richness of stochastic phenomena, how it arises from the interactions of dynamics and noise, and its biological implications.
LernzielTo understand the origins and implications of stochastic noise in living cells, and to learn the computational tools for the modeling, simulation, analysis, and identification of stochastic biochemical reaction networks.
InhaltThe cellular environment is abuzz with noise. A key source of this noise is the randomness that characterizes the motion of cellular constituents at the molecular level. Cellular noise not only results in random fluctuations (over time) within individual cells, but it is also a main source of phenotypic variability among clonal cell populations.

Review of basic probability and stochastic processes; Introduction to stochastic gene expression; deterministic vs. stochastic models; the stochastic chemical kinetics framework; a rigorous derivation of the chemical master equation; moment computations; linear vs. nonlinear propensities; linear noise approximations; Monte Carlo simulations; Gillespie's Stochastic Simulation Algorithm (SSA) and variants; direct methods for the solution of the Chemical Master Equation; moment closure methods; intrinsic and extrinsic noise in gene expression; parameter identification from noise; propagation of noise in cell networks; noise suppression in cells; the role of feedback; exploiting noise; bimodality and stochastic switches.
LiteraturLiterature will be distributed during the course as needed.
Voraussetzungen / BesonderesStudents are expected to have completed the course `Mathematical modeling for systems biology (BSc Biotechnology) or `Computational systems biology (MSc Computational biology and bioinformatics). Concurrent enrollment in `Computational Systems Biology: Deterministic Approaches is recommended.
636-0301-00LCurrent Topics in Biosystems Science and Engineering2 KP1SR. Platt, N. Beerenwinkel, Y. Benenson, K. M. Borgwardt, P. S. Dittrich, M. Fussenegger, A. Hierlemann, D. Iber, M. H. Khammash, D. J. Müller, S. Panke, S. Reddy, T. Schroeder, T. Stadler, J. Stelling, B. Treutlein, C. Uhler
KurzbeschreibungThis seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology.
LernzielTo provide an overview of current systems biology research.
InhaltThe final list of topics will be available at
636-0704-00LComputational Biology and Bioinformatics Seminar2 KP2SJ. Stelling, D. Iber, M. H. Khammash, J. Payne, T. Stadler, C. Uhler
KurzbeschreibungComputational Biology und Bioinformatik analysieren lebende Systeme mit Methoden der Informatik. Das Seminar kombiniert Präsentationen von Studierenden und Forschenden, um das sich schnell entwickelnde Gebiet aus der Informatikperspektive zu skizzieren. Themenbereiche sind Sequenzanalyse, Proteomics, Optimierung und Bio-inspired computing, Systemmodellierung, -simulation und -analyse.
LernzielStudying and presenting fundamental papers of Computational Biology and Bioinformatics. Learning how to make a scientific presentation and how classical methods are used or further developed in current research.
InhaltComputational biology and bioinformatics aim at advancing the understanding of living systems through computation. The complexity of these systems, however, provides challenges for software and algorithms, and often requires entirely novel approaches in computer science. The aim of the seminar is to give an overview of this rapidly developing field from a computer science perspective. In particular, it will focus on the areas of (i) DNA sequence analysis, sequence comparison and reconstruction of phylogenetic trees, (ii) protein identification from experimental data, (iii) optimization and bio-inspired computing, and (iv) systems analysis of complex biological networks. The seminar combines the discussion of selected research papers with a major impact in their domain by the students with the presentation of current active research projects / open challenges in computational biology and bioinformatics by the lecturers. Each week, the seminar will focus on a different topic related to ongoing research projects at ETHZ, thus giving the students the opportunity of obtaining knowledge about the basic research approaches and problems as well as of gaining insight into (and getting excited about) the latest developments in the field.
LiteraturOriginal papers to be presented by the students will be provided in the first week of the seminar.