Identification of Eigen-genes, consensus modules and Network Motifs in co-expression (or other biological) networks. (Webinar)
Organizer: University of Cambridge
Host institution: University of Cambridge Bioinformatics Training
Start: Monday, 10 August 2020 @ 10:00
End: Monday, 10 August 2020 @ 12:00
Venue: Craik-Marshall Building
Country: United Kingdom
Postcode: CB2 3ARTarget audience:
- This webinar is suitable for students and early career researchers with interest in Genomics
- Graduate students
- Postdocs and Staff members from the University of Cambridge
- Institutions and other external Institutions or individuals.
- <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">.
One of the most important tasks of systems biology is to create explanatory and predictive models of complex biological systems. Availability of gene expression data in different conditions has paved the way for reconstructing direct or indirect regulatory connections between various genes and gene products. Most often, we are not interested in single interactions between gene products; instead, we try to reconstruct networks that provide insights into the investigated biological processes or the entire system as a whole.
This webinar will expand upon the concept of Gene Co-expression Networks to elucidate Weighted Gene Co-expression Network Analysis (WGCNA), and introduce the importance of visualising clustered gene expression profiles as single ‘Eigengenes’. It will describe the complete protocol for WGCNA analysis starting from normalised Gene Expression Datasets (Microarrays or RNA-Seq). This will be followed by a discussion on methods of extraction and analysis of consensus modules and Network motifs from Gene Co-Expression Networks and Transcriptional Regulatory Networks.
The webinar will be presented in the form of a lecture and tutorial with screenshots that enable listeners to emulate the protocols in R. Note that this is a webinar and not a coding exercise. Links to further reading and practice will be shared.
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