Gene Regulatory Networks for Development

This course introduces the concepts of Gene regulatory networks (GRNs), and teaches experimental and computational methods used to study them, through highly interactive lectures, discussions, group projects, and practical tutorials.

Course date: TBD
Application due date: TBD

The Gene Regulatory Networks course is on hiatus with an expected return in 2023.

Directors: Scott Barolo, University of Michigan; and Isabelle Peter, California Institute of Technology

Course Description

Gene regulatory networks (GRNs) are key to the genomic control of development in animals and plants. To study GRNs requires insights from various research fields, including systems biology, developmental and evolutionary biology, as well as functional genomics, and provides an integrative approach to fundamental research questions in biology. This course introduces the concepts of GRNs, and teaches experimental and computational methods used to study them, through highly interactive lectures, discussions, group projects, and practical tutorials. We will cover a broad range of topics, including transcriptional control systems, the structural organization of hierarchical networks, developmental functions of GRN circuit modules, GRN evolution, and computational modeling using BioTapestry as well as Boolean and quantitative mathematical approaches. Students will learn how to generate GRN models based on data extracted from the literature, and will generate computational models to analyze dynamic circuit behavior. We will present and discuss a broad range of experimental approaches and how they are effectively used for studying gene regulation and developmental GRNs. Examples of experimentally solved developmental GRNs from a variety of organisms, such as flies, sea urchins, frogs, chicken, and mice, will be explored. Students are encouraged to share their research projects in a poster session, and to discuss with course faculty how to apply the approaches taught in the course to their own research questions. The course is intended for advanced graduate students, postdoctoral scholars, and faculty.