Data Mining and Network Analysis
BSR6803.01 Systems Biology of Disease and Therapeutics CMC (customized mini-course)

Course Director: Avi Ma'ayan PhD

Course Description
Cell signaling and gene regulatory networks are the focus of biomedical research because such complex systems control cellular behavior. In the past several decades, cell and molecular biologists have accumulated enormous amounts of knowledge about cell regulation; however, many components and details about their interactions, particularly in mammalian cells, are still largely unknown. Hence, we still do not have a holistic understanding of cellular regulation. There is a knowledge gap. However, the rate of data accumulation resulting from emerging high-throughput biotechnologies has the premise to close this knowledge gap, but integrating data from multiple sources to extract real knowledge about regulatory networks and developing new hypotheses and new theories is a major challenge. In this mini-course we will discuss methods used to analyze the topology of biological regulatory networks; we will survey several machine learning approaches and how they are applied to study biological molecular networks; we will discuss papers that combine computational predictions with experimental validation; and use software tools to analyze proteomics and genomics experimental expression data.

Course Schedule Fall 2011

Date Topic Assigned Papers
9/27 Self Organizing Maps PMID: 20202218
10/4 Network Analysis in Systems Biology PMIDs: 10521342, 9623998
10/11 Network Analysis in Systems Biology PMID: 21917719
10/18 Network Analysis in Systems Biology PMID: 21917719
10/25 Decision Tree Classifiers Machine Learning 1:81-106
11/1 Analysis of Microarray and RNA-seq Data
11/8 SVM Classifiers PMID: 18974822
11/22 PCA PMIDs: 20709693, Paper1
11/29 Gene Set Enrichment Analysis PMIDs: 16199517, 21917718
12/6 Unsupervised Clustering of K-Partite Graphs References: Paper1, Paper2
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