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8 materials found

Authors: Gary Bader  or Jeff Xia 

Pathways and Network Analysis of -Omics data 2018 Module 3-Network Visualization and Analysis with Cytoscape

Course covers the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information.

Pathways and Network Analysis of -Omics Data 2018 Module 1-Introduction to Pathway and Network Analysis

Course covers the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information.

Informatics and Statistics for Metabolomics 2018 Module 5-MetaboAnalyst

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics Module 4-Backgrounder in Statistics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Pathways and Network Analysis of -Omics Data 2017 Module 3-Network Visualization and Analysis with Cytoscape

Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.

Pathways and Network Analysis 2017 Module 2-Finding Over-Represented Pathways

Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.

Pathways and Network Analysis of -Omics Data 2017 Module 1-Introduction to Pathway and Network Analysis

Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.

Informatics and Statistics for Metabolomics 2017 Module 4-Backgrounder in Statistics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.