Browsing by Subject "Alternative Splicing"

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    Alt Event Finder: a tool for extracting alternative splicing events from RNA-seq data.
    (BMC, 2012) Zhou, Ao; Breese, Marcus R.; Hao, Yangyang; Edenberg, Howard J.; Li, Lang; Skaar, Todd C.; Liu, Yunlong
    BACKGROUND: Alternative splicing increases proteome diversity by expressing multiple gene isoforms that often differ in function. Identifying alternative splicing events from RNA-seq experiments is important for understanding the diversity of transcripts and for investigating the regulation of splicing. RESULTS: We developed Alt Event Finder, a tool for identifying novel splicing events by using transcript annotation derived from genome-guided construction tools, such as Cufflinks and Scripture. With a proper combination of alignment and transcript reconstruction tools, Alt Event Finder is capable of identifying novel splicing events in the human genome. We further applied Alt Event Finder on a set of RNA-seq data from rat liver tissues, and identified dozens of novel cassette exon events whose splicing patterns changed after extensive alcohol exposure. CONCLUSIONS: Alt Event Finder is capable of identifying de novo splicing events from data-driven transcript annotation, and is a useful tool for studying splicing regulation.
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    A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra
    (Oxford, 2017-05-01) Kou, Qiang; Wu, Si; Tolić, Nikola; Paša-Tolić, Ljiljana; Liu, Yunlong; Liu, Xiaowen; BioHealth Informatics, School of Informatics and Computing
    Motivation: Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a 'bird's eye view' of intact proteoforms. The combinatorial explosion of various alterations on a protein may result in billions of possible proteoforms, making proteoform identification a challenging computational problem. Results: We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry datasets showed that TopMG outperformed existing methods in identifying complex proteoforms.