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홈 > 학술정보 >학술행사 > 세미나
2017 KAIST Math. Colloquium

Title
Statistical and computational approaches to extracting information from high-throughput sequencing data in genomics applications
Speaker
심희정   (University of Melbourne )
Date
2017-12-19 16:15:00
Host
KAIST
Place
자연과학동(E6) Room 1501
Abstract
Analyses of molecular phenotypes, such as gene expression, transcription factor binding, chromatin accessibility, and translation, is an important part of understanding the molecular basis of gene regulation and eventually organismal-level phenotypes, such as human disease susceptibility. The development of cheap high-throughput sequencing (HTS) technologies with experiment protocols has increased the use of HTS data as measurements of the molecular phenotypes (e.g., RNA-seq, ChIP-seq, and ATAC-seq). The HTS data provide high-resolution measurements across the whole genome that represent how the molecular phenotypes vary along the genome. We develop multiple statistical methods that better exploit the high-resolution information in the data and apply them to different biological questions in genomics. In this talk, I will briefly introduce two projects: 1) wavelet-based methods for identification of genetic variants associated with chromatin accessibility, and 2) mixture of hidden Markov models for inference of translated coding sequences.
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