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    Computational Challenges in Proteomics: from Short Peptides to Long Intact Proteins
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    Update time: 2012-06-01
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    Speaker: Dr. Xiaowen Liu, University of California
    Inviter: Prof. Bu Dongbo, Center for Advanced Computing Research, ICT
    Time: 16:30pm—17:30pm, June 1st, 2012 (Friday)
    Place: Room 1201, Institute of Computing Technology, Chinese Academy of Sciences
    Abstract:
    In traditional research of distributed problems, two types of failures are commonly considered: While the genome provides the blueprint of gene products, proteins are the bricks and mortar of biology. Mass spectrometry (MS) is the core technology for the study of proteins, their post-translational modifications, and their interactions. Over the past decade, proteomics has been dominated by bottom-up MS that digests proteins into fragments and analyzes the resulting short peptides. Since information about intact proteins is lost during digestion, recent studies advocated top-down MS that analyzes intact proteins and gives rise to many computational challenges. While top-down MS researchers have made great progress in the last two years, the algorithms for interpreting top-down MS data are still in their infancy. We describe new combinatorial algorithms for the analysis of top-down MS data and show how they enable new biological applications.
    Bio:
    Xiaowen Liu received his Ph.D. degree in computer science from the City University of Hong Kong in 2008. He worked as a postdoc at the University of Western Ontario and the University of Waterloo from 2008 to 2009. He is a postdoc at the University of California, San Diego. His research area is algorithmic biology. During the past three years, he worked on solving algorithmic problems in computational proteomics.
     

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