Reading materials

Reading materials

This page contains recommended reading materials in addition to the pre-course content.

! - important

Machine Learning approaches in Integration
Note: if you cannot see one of the pages because you’ve reached the free member preview, open the page in “Private Browsing” mode in your web browser. - ! Feature selection - ! Dimensionality reduction - ! Supervised Omics integration - ! Unsupervised Omics integration - Multi-omics approaches to disease

Biological Network Analysis and Network Topology - ! Network biology: understanding the cell’s functional organization - ! Network medicine: a network-based approach to human disease - Network biology concepts in complex disease comorbidities - Gene co-expression analysis and conserved modules

Genome-scale metabolic modeling - ! Overview of genome-scale metabolic models - What is flux balance analysis? - A Systematic Evaluation of Methods for Tailoring Genome-Scale Metabolic Models - Human Metabolic Models: Human1 and Recon3D - ! Reporter metabolite analysis - Gene set enrichment analysis (GSEA) and Directional gene set analysis (GSA) - Modeling software: Python: COBRApy, MATLAB: RAVEN and COBRA

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