Coursera - Icahn School of Medicine - Introduction to Systems Biology

10 weeks | 6-8 hours/week | MP4 | VP8, 960x540, 25fps | Vorbis | 2 chs 48Khz | 1.69GB

Genre: E-learning

This course will introduce the student to contemporary Systems Biology focused on mammalian cells, their constituents and their functions. Biology is moving from molecular to modular. As our knowledge of our genome and gene expression deepens and we develop lists of molecules (proteins, lipids, ions) involved in cellular processes, we need to understand how these molecules interact with each other to form modules that act as discrete functional systems. These systems underlie core subcellular processes such as signal transduction, transcription, motility and electrical excitability. In turn these processes come together to exhibit cellular behaviors such as secretion, proliferation and action potentials. What are the properties of such subcellular and cellular systems? What are the mechanisms by which emergent behaviors of systems arise? What types of experiments inform systems-level thinking? Why do we need computation and simulations to understand these systems?

The course will develop multiple lines of reasoning to answer the questions listed above. Two major reasoning threads are: the design, execution and interpretation of multivariable experiments that produce large data sets; quantitative reasoning, models and simulations. Examples will be discussed to demonstrate “how” cell- level functions arise and “why” mechanistic knowledge allows us to predict cellular behaviors leading to disease states and drug responses.

Course Syllabus

Topics covered include:

Systems Level Reasoning: Bottom-Up and Top-Down Approaches for Complex Systems

Cell Signaling Pathways: Molecules to Pathways, cAMP and MAP-kinase Pathways

Signal Flow: Pathways to Networks

The Actin Cytoskeleton: The Cell Motility Machine

Mathematical Representations of Cell Biological Systems Time and Space

Gathering Large Data Sets in Genomics and Proteomics

Inferring Modules: Computational Analysis of Large Data Sets; Building Networks

Small Scale Systems Biology Experiments

Identifying Emergent Properties by Computation: Dynamical Models

Emergent Properties: Ultrasensitivity, Bistability, Robustness and Fragility

Modules to Functions: Control Systems

Module-Boundaries: Sharp and Fuzzy, Interactions between Subcellular Modules

Emergence of Cellular Functions from Subcellular Modules

Systems Analysis of Complex Diseases

Systems Pharmacology: Understanding Drug Action from a Systems Perspective