博碩士論文 91522078 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator李英準zh_TW
DC.creatorYing-Chun Leeen_US
dc.date.accessioned2004-7-12T07:39:07Z
dc.date.available2004-7-12T07:39:07Z
dc.date.issued2004
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=91522078
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract在人類基因體序列中,至少有45%的區域屬於跳躍子(Transposable Elements),造成如此大量的原因,與它們在基因體內移動的行為有關,而它們可能隱含了遺傳演化,及基因體增加適應性及變異性的原因。長終端重覆序列反轉錄跳躍子(long terminal repeat retrotransposons)是一個很重要的一類跳躍子,它們有完整的結構及功能,長終端重覆序列中包含有功能的調控區域,我們相信這些重要的區域會在演化過程中保留下來,因此我們在已知的長重覆終端序列上搜尋這些重要的區域,以隱藏馬可夫模型(Hidden Markov Model)代表這些區域,使用這些模型作為辨認基礎,我們可以辨認大部份已知的長重覆終端序列,並正確地分辨各族群,不但能處理結構完整的情況,也能偵測出新的長重覆終端序列,供遺傳演化上之研究。zh_TW
dc.description.abstractMore then 45% of human genome was annotated as transposable elements (TEs). The expansion of the human genome is resulted from the mobilization of these TEs and they may increase the plasticity and variation in our genome. Long terminal repeat (LTR) retrotransposons are major components in TEs. There are regulatory sites in LTR and we believe that they could be conserved in evolution. Therefore, we search for these significant motifs in the sequence of LTRs and these motifs are used to train Hidden Markov Model (HMM). Using these models as fingerprints, we can detect most of the known LTRs detected by RepeatMasker and LTR instances are classified into families using the predictive models proposed. It could be helpful for evolution analysis.en_US
DC.subject隱藏馬可夫模型zh_TW
DC.subject跳躍子zh_TW
DC.subject長終端重覆序列zh_TW
DC.subject生物資訊zh_TW
DC.subjectbioinformaticsen_US
DC.subjectlong terminal repeatsen_US
DC.subjecttransposable elementsen_US
DC.subjectHidden Markov Modelsen_US
DC.title使用隱藏馬可夫模型偵測人類基因體序列上之長終端重覆序列結構zh_TW
dc.language.isozh-TWzh-TW
DC.titleDetection of LTR Structures in Human Genomic Sequences Using Profile Hidden Markov Modelsen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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