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Experimental Methods in Systems Biology

Offered By: Icahn School of Medicine at Mount Sinai via Coursera

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Biology Courses Data Analysis Courses Systems Biology Courses RNA Sequencing Courses Flow Cytometry Courses Computational Modeling Courses

Course Description

Overview

Learn about the technologies underlying experimentation used in systems biology, with particular focus on RNA sequencing, mass spec-based proteomics, flow/mass cytometry and live-cell imaging. A key driver of the systems biology field is the technology allowing us to delve deeper and wider into how cells respond to experimental perturbations. This in turns allows us to build more detailed quantitative models of cellular function, which can give important insight into applications ranging from biotechnology to human disease. This course gives a broad overview of a variety of current experimental techniques used in modern systems biology, with focus on obtaining the quantitative data needed for computational modeling purposes in downstream analyses. We dive deeply into four technologies in particular, mRNA sequencing, mass spectrometry-based proteomics, flow/mass cytometry, and live-cell imaging. These techniques are often used in systems biology and range from genome-wide coverage to single molecule coverage, millions of cells to single cells, and single time points to frequently sampled time courses. We present not only the theoretical background upon which these technologies work, but also enter real wet lab environments to provide instruction on how these techniques are performed in practice, and how resultant data are analyzed for quality and content.

Syllabus

  • Introduction
    • Description goes here
  • Deep mRNA Sequencing
    • Description goes here
  • Mass Spectrometry-Based Proteomics
    • Description goes here
  • Midterm Exam
    • Description goes here
  • Flow and Mass Cytometry for Single Cell Protein Levels and Cell Fate
    • Description goes here
  • Live-cell Imaging for Single Cell Protein Dynamics
    • Description goes here
  • Integrating and Interpreting Datasets with Network Models and Dynamical Models
    • Description goes here
  • Final Exam

Taught by

Marc Birtwistle

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