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中科院计算生物学重点实验室学术报告:Understanding the non-coding genome

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时间:2017-12-07  来源:文本大小:【 |  | 】  【打印

Speaker: Xin Li, PhD
          Postdoctoral Fellow, (Dr. Stephen Montgomery) Stanford University, Department of Pathology

Time : 10:00-12:00 am , Dec. 12(Tuesday)
Venue: Room 300, SIBS Main Building, Yueyang Road 320
Host: Prof. Zefeng Wang
        CAS-MPG Partner Institute for Computational Biology

Fields of Interest:
        Functional genomics, non-coding variation, precision medicine, bioinformatics

Education:
        Ph.D. Computer Science, Case Western Reserve University, 2005-2010.
        Thesis: Haplotype Inference from Pedigree Data and Population Data 
        B.S. Computer Science, Tsinghua University, 2001-2005.
        Thesis: Heuristic algorithms for Steiner minimum spanning tree

 

Title:Understanding the non-coding genome

 

Abstract:
        Non-coding regions account for over 98% of the human genome, constituting important yet largely unknown gene regulatory functions. GWAS studies have found that the vast majority of the associated loci for complex diseases such as cardiovascular diseases, diabetes, and cancer fall in non-coding regions. However unlike the protein-coding sequence where there is a clear genetic code, we have little knowledge how DNA sequences specify regulatory functions. Recent development in high-throughput technology has made it possible to query multiple cascades of transcriptome activity, from chromatin accessibility/states, mRNA initiation/splicing to post-transcriptional modification. My work is to explore these multi-omics data resources to build a comprehensive map of functional variation and their association with disease. We demonstrate that new computational approaches combining genomic and functional genomic data are of exceptional utility to unlock the non-coding genome.

       

        All are welcome!

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