Understanding Genotype-Phenotype Relations via Network Approaches

Distinguished Lecture in Causal Discovery
Center for the Neural Basis of Cognition (CNBC)

Understanding Genotype-Phenotype Relations via Network Approaches

Senior Investigator, Algorithmic Methods in Computational and Systems Biology (AlgoCSB)
National Center for Biotechnology Information, National Institutes of Health
December 3, 2015 - 11:00am
Classroom 407a/b BAUM, 4th floor, 5607 Baum Blvd - or remote viewing

Location: Classroom 407a/b BAUM, 4th floor, 5607 Baum Blvd - remote viewing below

When: Thursday, December 03, 2015 11:00 AM – 12:00 PM

Organizer: Porterfield, Toni

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Teresa M. Przytycka, PhD, Senior Investigator, Algorithmic Methods in Computational and Systems Biology (AlgoCSB), National Center for Biotechnology Information, National Institutes of Health, will deliver the Distinguished Lecture in Causal Discovery, “Understanding Genotype-Phenotype Relations via Network Approaches,” at 11:00 am on Thursday, December 3, 2015, in the Rooms 407A/B BAUM, 5607 Baum Blvd., The Offices at Baum. Abstract: Uncovering and interpreting phenotype--genotype relationships are among the most challenging open questions in disease studies. In cancer, these relationships are additionally obscured by heterogeneity of the disease. Pathway-centric approaches have emerged as methods that can empower studies of heterogeneous diseases. Using such network based approaches we designed methods that allow detection of subnetworks dysregulated in cancer, and to establish associations gene expression and genotype. Our approaches build on variety of algorithmic techniques including graph-theoretical techniques (module cover) and on machine learning topic model approach (probabilistic genotype-phenotype model) and information flow. I will demonstrate the utility of our methods using TCGA (The Cancer Genome Atlas) data. Biography: Teresa Przytycka is a Senior Investigator in the Computational Biology Branch at National Center of Biotechnology Information, NIH and heads the Computational Methods in Molecular and Systems Biology section. Dr. Przytycka received her PhD in Computer Science Department at University of British Columbia Vancouver where she focused on theory of algorithms. She did her postdoctoral work in Department of Biophysics, Johns Hopkins University studying protein folding. She was a recipient of I.W. Killam Memorial Fellowship, Sloan Foundation and the U.S. Department of Energy Fellowship in Computational Biology, and Burroughs Wellcome Fellowship in Computational Biology. Dr. Przytycka serves as a Deputy Editor of the Bioinformatics Section of Nature Molecular Therapy Nuclide Acids and as an Associate Editor for PloS Computational Biology, BMC Bioinformatics, IEEE Transactions on Computational Biology and Bioinformatics, and Algorithms for Molecular Biology. Research in her group focuses on dynamical properties of biological systems including spatial, temporal and contextual variations and exploring how such variations are impacting gene expression, functioning of biological pathways, and the phenotype of organisms. Her group developed several new approaches to study pathways dysregulated in cancer, gene regulation, and analysis of massive HT-SELEX data.