- Platform
- Coursera
- Provider
- Icahn School of Medicine at Mount Sinai
- Effort
- 6 to 8 hours per week
- Length
- 10 weeks
- Language
- English
- Credentials
- Paid Certificate Available
- Part of
- Course Link
Overview
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.
Taught by
Ravi Iyengar
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.
Syllabus
- Systems Level Reasoning | Molecules to Pathways
- Pathways to Networks | Physical Forces and Electrical Activity in Cell Biology
- Mathematical Representations of Cell Biological Systems | Simulations of Cell Biological Systems
- Experimental Technologies | Network Building and Analysis
- Midterm
- Analysis of Networks | Topology to Function
- Strengths and Limitations of Different Types of Models | Identifying Emergent Properties
- Emergent Properties: Ultrasensitivity and Robustness | Case Studies
- Case Studies | Systems Biomedicine | Systems Pharmacology and Therapeutics | Perspective
- Final
Taught by
Ravi Iyengar