“ST-Steiner: A Spatio-Temporal Gene Discovery Algorithm” by Ercument Cicek (Bilkent, Computer Engineering)
Date: Wednesday, 27 March, 2019
Time: 1240 – 1330
Place: A-130
Organized by the Mind, Brain and Behavior Research Group at Bilkent University.
Abstract: Whole exome sequencing (WES) studies for Autism Spectrum Disorder (ASD) could identify only around six dozen risk genes to date because the genetic architecture of the disorder is highly complex. To speed the gene discovery process up, a few network-based ASD gene discovery algorithms were proposed. Although these methods use static gene interaction networks, functional clustering of genes is bound to evolve during neurodevelopment and disruptions are likely to have a cascading effect on the future associations. Thus, approaches that disregard the dynamic nature of neurodevelopment are limited in power. In this talk, I will present a spatio-temporal gene discovery algorithm for progressive disorders, which leverages information from evolving gene coexpression networks. in the context of ASD, the algorithm solves an adapted prize collecting Steiner forest based problem on coexpression networks to model neurodevelopment and transfer information from precursor neurodevelopmental windows. The decisions made by the algorithm can be traced back, adding interpretability to the results. We apply the algorithm on WES data of 3,871 samples and identify risk clusters using BrainSpan coexpression networks of early- and mid-fetal periods. On an independent dataset, we show that incorporation of the temporal dimension increases the predictive power: Predicted clusters are hit more and show higher enrichment in ASD-related functions compared to the state-of-the-art.
About the speaker: Ercument Cicek earned his BS and MS degrees in Computer Science and Engineering from Sabanci University. He received his Ph.D. degree in Computer Science from Case Western Reserve University in 2013. During his Ph.D., he visited Cold Spring Harbor Laboratory to work on gene discovery algorithms for Autism Spectrum Disorder. After graduation, he worked as a Lane Fellow in Computational Biology at Carnegie Mellon University till 2015. Since then, he is an assistant professor in the Computer Engineering Department of Bilkent University and is an adjunct faculty member in the Computational Biology Department of Carnegie Mellon University. Short bio: Ercument Cicek earned his BS and MS degrees in Computer Science and Engineering from Sabanci University. He received his Ph.D. degree in Computer Science from Case Western Reserve University in 2013. During his Ph.D., he visited Cold Spring Harbor Laboratory to work on gene discovery algorithms for Autism Spectrum Disorder. After graduation, he worked as a Lane Fellow in Computational Biology at Carnegie Mellon University till 2015. Since then, he is an assistant professor in the Computer Engineering Department of Bilkent University and is an adjunct faculty member in the Computational Biology Department of Carnegie Mellon University.
Web: www.phil.bilkent.edu.tr
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