中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/29114
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 78728/78728 (100%)
Visitors : 33547981      Online Users : 1308
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29114


    Title: Detecting LTR structures in human genomic sequences using profile hidden Markov models
    Authors: Wu,LC;Huang,HD;Chang,YC;Lee,YC;Horng,JT
    Contributors: 資訊工程研究所
    Keywords: ELEMENTS;IDENTIFICATION;RETROTRANSPOSONS;DATABASE
    Date: 2009
    Issue Date: 2010-06-29 20:14:03 (UTC+8)
    Publisher: 中央大學
    Abstract: More than 45% of human genome has been annotated as transposable elements (TEs). The human genome is expanded by the mobilization of these TEs, which they may increase the plasticity and variation of the genome. Long terminal repeat (LTR) retrotransposons are important components in TEs. LTRs include regulatory sites, which the authors believe could be conserved in evolution. Therefore, these significant motifs in the sequence of LTRs are found and are used to train a Hidden Markov Model. These models are used as fingerprints to detect most of the known LTRs detected by RepeatMasker. LTR instances are classified into families using the predictive models proposed. These LTRs can support evolutionary analysis. A new method of detecting LTR is proposed. Analyzing LTR sequences reveals some specific motifs as LTR fingerprints, which can be built into HMM profiles. Experimental results reveal that the proposed experimental approach not only discovers most of the LTRs found by RepeatMasker, but also detects some novel LTRs. Moreover, the novel LTRs may be structurally incomplete or degenerate. (C) 2008 Published by Elsevier Ltd.
    Relation: EXPERT SYSTEMS WITH APPLICATIONS
    Appears in Collections:[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML518View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明