June 24-26, 2020
Most biological systems are structured as networks – from molecular signaling and metabolic networks to immune cell and neural networks to vast networks of social and environmental interactions. Elucidating these networks is key not only to our biological understanding, but also to the next generation of patient data analysis, diagnosis and therapy. For these reasons, much of recent technology development has focused on mapping biological networks at multiple scales, resulting in an expansive collection of network data and ways in which networks are becoming instrumental in biological and clinical studies. This course teaches an understanding of the types, roles, and uses of networks in the biomedical sciences. It covers theory and practice of network analysis through classroom discussions, reading assignments, and project-oriented problem sets using tools such as Python and Cytoscape.
University of Notre Dame
UC San Diego
• Be familiar with basic network terminology
• Be able to navigate large datasets in R/Python
• Prior exposure to basic genetics and statistical analysis is strongly recommended.
This course will involve some conceptual and some mathematical components. It will involve hands-on teaching utilizing Cytoscape, Python and NetworkX software.
About the instructors
Tijana Milenkovic is an Associate Professor of Computer Science and Engineering at the University of Notre Dame. She has been a Notre Dame faculty since 2010, after earning a Ph.D. degree in Computer Science from the University of California Irvine (UCI) in the same year. Prior to that, she earned a M.Sc. degree in Computer Science from UCI in 2008, and a B.Sc. degree in Electrical Engineering and Computer Science from the University of Sarajevo in 2005.
Milenkovic lab solves challenging problems in the fields of network science, graph algorithms, computational biology, scientific wellness, and social networks. Milenkovic won prestigious 2015 National Science Foundation (NSF) CAREER and 2016 Air Force Office of Scientific Research (AFOSR) Young Investigator Program (YIP) awards, among others. She will serve on the Board of Directors of the International Society for Computational Biology (ISCB) during 2020-2023, representing the Society's Communities of Special Interest (COSIs). She has been an Associate Editor of IEEE/ACM TCBB since 2014 and of Nature's Scientific Reports since 2018. Milenkovic is committed to increasing participation of women and diversity in computer science.
Trey Ideker, Ph.D. is a Professor in the Departments of Medicine, Bioengineering and Computer Science at UC San Diego, and Director or co-Director of three NIH-supported research centers: the NIGMS National Resource for Network Biology, the NCI Cancer Cell Map Initiative, and the NIMH Psychiatric Cell Map Initiative. Dr. Ideker received Bachelor’s and Master’s degrees from MIT in Electrical Engineering and Computer Science and his Ph.D. from the University of Washington in Molecular Biology under the supervision of Dr. Leroy Hood.
Dr. Ideker is a pioneer in using genome-scale measurements to construct network models of cellular processes and disease and has founded software tools including the Cytoscape ecosystem for biological network analysis, which has been cited >13,000 times. Dr. Ideker serves on the Editorial Boards for Cell, Cell Reports, Molecular Systems Biology, and PLoS Computational Biology and is a Fellow of AAAS and AIMBE. He was named a Top 10 Innovator by Technology Review and was the recipient of the Overton Prize from the International Society for Computational Biology. His work has been featured in news outlets such as The Scientist, San Diego Union-Tribune, Forbes magazine, NPR, and The New York Times.