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636-0016-00L 4 Credits DR , MSC D-BSSE , D-INFK
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Computational Systems Biology: Stochastic Approaches

Lecturers & Examiners: Prof. Dr. Mustafa Hani Khammash, Dr. Ankit Gupta
VVZ CR n/a

Last Updated: 2026-06-01 11:30:45

Abstract

This 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.

Objective

To 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.

Content

The 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.

Resources

Literature

Literature will be distributed during the course as needed.

General Information

Language
English
Levels
DR , MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 180 minutes
Aids
None

Course Components

Type Title Time & Place Hours
lecture with exercise Computational Systems Biology: Stochastic Approaches
The lecture is held at the D-BSSE in Basel and transmitted per video conference to Zürich (HCI G7). The lecture starts in the second week of the semester.
  • Mon 13:45-16:30 (HCI G 7)
  • Mon 14:15-17:00 (BSS E 23)
  • 04.11 Date 14:15-17:00 (BSS E 23)
3 h weekly

Offered In

  • Computational Biology and Bioinformatics Master (Weitere Informationen: )
    • Kernfächer (Die Liste der Kernfächer ist eine geschlossene Liste - es können keine anderen Kurse in dieser Kategorie hinzugefügt werden. Die Zuordnung der Kurse zu der jeweiligen Unterkategorie kann nicht geändert werden. Studierende müssen mindestens einen Kurs pro Unterkategorie bestehen. Insgesamt müssen 40 ECTS Kernfächer erworben werden, einschliesslich des obligatorischen CBB-Seminars.)
  • Doktorat Biosysteme (Mehr Informationen unter: Für Kurse der Kategorie "Integration in die wissenschaftliche Gemeinschaft" bitte die BSSE Webseite konsultieren: )
  • Biotechnologie Master (Weitere Informationen: )
    • Wahlfächer (Offene Liste - weitere Kurse (ETH oder UNIBAS) können nach Absegnung durch den:die Mentor:in als Wahlfächer gewählt werden.)