Program Name: Biomedical Sciences
Course Name: BD2K Data Mining and Network Analysis Course Id: 6803
Cell signaling and gene regulatory networks are the focus of biomedical research since such complex systems control cellular behavior. The rate of data accumulation resulting from emerging high-throughput biotechnologies has the premise to significantly advance our understanding of such complex systems. However, integrating data from multiple sources to extract real knowledge about these regulatory networks, and developing new hypotheses and new theories about how these networks work is still a major challenge. The course covers various data mining methods and strategies applied to biological data in broad areas of systems biology and systems pharmacology. Topics covered include supervised learning, unsupervised clustering methods, and graph theory. Topics include: network based classifiers, decision trees, artificial neural networks, self-organizing maps, and linear regression as well as the shortest path algorithm, breadth and depth first search, and network motifs search. In additions methods to identify differentially expressed genes and perform gene set enrichment analyses will be covered.
Semester Offered: Fall
[print-me target= title=”Print Form”]