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Established in 2020, POSTECH Mathematical Institute for Data Science (MINDS) is the community of researchers in the areas of fundamental data science, machine learning, artificial intelligence, scientific computing, and humanitarian data science. MINDS mission is to provide a platform for collaboration among researchers and to provide various opportunities for students in data science. MINDS also aims to use our data science research to serve our local and global communities pursuing humanitarian data science.

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MINDS Seminar Series | Sun Young Shin (UT Dalla) - Scalable protein-DNA binding changer test for insertion and deletion of bases in the genome

MINDS SEMINAR
period : 2022-04-05 ~ 2022-04-05
time : 10:00:00 ~ 11:00:00
개최 장소 : Online streaming (Zoom)
Topic : Scalable protein-DNA binding changer test for insertion and deletion of bases in the genome
개요
Date 2022-04-05 ~ 2022-04-05 Time 10:00:00 ~ 11:00:00
Speaker Sun Young Shin Affiliation UT Dallas
Place Online streaming (Zoom) Streaming link ID : 688 896 1076 / PW : 54321
Topic Scalable protein-DNA binding changer test for insertion and deletion of bases in the genome
Contents Mutations in the noncoding DNA, which represents approximately 99\% of the human genome, have been crucial to understand disease mechanisms through dysregulation of disease-associated genes. One key element in gene regulation that noncoding mutations mediate is the binding of proteins to DNA sequences. Insertion and deletion of bases (InDels) are the second most common type of mutations, following single nucleotide polymorphisms, that may impact protein-DNA binding. However, no existing methods can estimate and test the effects of InDels on the process of protein-DNA binding. We develop a novel statistical test, named binding changer test (BC test), using a Markov model to evaluate the impact of InDels and identify InDels altering protein-DNA binding. The test predicts binding changer InDels of regulatory significance with an efficient importance sampling algorithm generating background sequences in favor of large binding affinity changes. Simulation studies demonstrate its excellent performance. The application to human leukemia data uncovers candidate pathologic InDels on modulating MYC binding in leukemic patients. We develop R package atIndel, which is available on GitHub.
MinDS MinDS · 2022-03-23 09:10 · Views 1312

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