Inference of Gene Regulatory Networks from Bulk and Single Cell Omic Datasets

Explore gene regulatory network inference techniques from bulk and single-cell omic datasets in this comprehensive lecture from the Computational Genomics Summer Institute 2022. Delve into the importance of regulatory networks, experimental mapping techniques, and various inference paradigms. Learn about expression-based network inference principles, integrative approaches, and prior-based methods. Examine predictive models of expression and their applications in identifying regulators of early lineage commitment and transcriptional dynamics during cellular reprogramming. Discover how single-cell genomics is revolutionizing biology and the incorporation of accessibility data in single-cell GRN inference. Gain insights into specific algorithms and methodologies, including Inferelator, Modified Elastic Net (MEN), MERLIN+P, and Symphony, while exploring related research papers for further understanding.

Intro
What is a regulatory network
Why do regulatory networks matter?
Expperimental techniques for mapping regulatory network components
Paradigms of network inference
Expression-based network inference basic principle
A non-exhaustive list of expression-based network inference method
Milestones in expression-based GRN inference
Integrative expression-based network inference
Prior-based approaches for network inference
Methods for incorporating auxiliary data
Inferelator: A parameter prior-based network inference algorithm
Modified Elastic Net (MEN)
MERLIN+P: A structure prior-based network inference algorithm
Network component analysis (NCA) for TFA estimation
A non-exhaustive list of integrative network inference methods
Basic principle of predictive models of expression
Inferring GRNs using predictive models of expression
Using Predictive models to identify regulators of early lineage commitment
Transcriptional dynamics during cellular reprogramming
Expression-based GRN inference vs Predictive models of expression
Single cell genomics is revolutionizing biology
Classes of network inference algorithms
Incorporating accessibility for single cell GRN inference
Symphony