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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/9631

    Title: 疾病相關基因探勘與預測
    Authors: 陳士農
    Contributors: 資訊學院
    Keywords: 疾病相關基因;選擇性剪接;資料探勘;智慧型代理人;樣式選擇;樣式權重;資訊擷取
    disease-related gene;alternative splicing;data mining;intelligent agent;pattern selection;pattern weighting;information retrieval;An Integrated System for
    Date: 2007
    Issue Date: 2010-05-13 15:11:47 (UTC+8)
    Abstract: 在人類基因體計畫(Human Genome Project)完成定序後,越來越多的人投入生物資訊(Bioinformatics)的研究行列,不管是在序列的預測、藥物的研發或是疾病的治療等,都是重要的研究課題。本計畫提出一個疾病相關基因探勘與預測之整合系統,提供收集文獻資料並且提供查詢疾病相關基因的選擇性剪接(alternative splicing)資訊。本方法能提供生物醫學研究人員在生物實驗驗證時的相關資訊,縮短生物實驗驗證的時間。使用者可以輸入基因名稱(gene name)、去氧核醣核酸序列(DNA sequence),並選擇疾病相關基因的權重矩陣(weight matrix),經由系統分析與預測後,輸出疾病相關資訊,像是完整的基因序列、mRNA、內子(intron)、外子(exon)、選擇性剪接、摘要報告等,並以圖形介面輸出。
    After the Human Genome Project is completed, more and more researchers involve in the research of bioinformatics. No matter the prediction of sequence, research and development of medicine or treatment of the disease etc. are all important research subjects. This proposal proposes an integrated system for disease-related genes mining and prediction from biomedical literatures. This system can collect the biomedical literatures and query the alternative splicing information of disease-related genes. This research can provide the relevant information to the biologists and shorten the time for the verification of biological experiment. The user can input gene name, DNA sequence, any compound words, or documents, then select the weight matrix. After it is analyzed and predicted by the system, it can output the disease-related information, such as complete disease gene sequence, mRNA, intron, exon, alternative splicing, summary report, etc., and showed by the graphic interface.
    To use keywords search for literatures, someone might suffer from the difficulty that user must be somewhat familiar with the topics user concerning with such that user could specify the patterns (or terms) with highlight as keywords. In this proposal, we proposed document query to search literatures for the users who have no prior knowledge to specify keywords, but only with one document they is interesting. To achieve this goal with reliable search results and short response time for query processes, all of the documents are transformed as vectors according to selected patterns with proper weighting in advance. The similarities are evaluated by measuring the distance between the vectors. The documents will be ranked orderly according to the values of the similarities between them and the query document if the similarities are greater than a given threshold. We plan to select the related bioinformatics terms, such as genes or proteins names, as representative patterns and to tune their weighting according the statistics of frequency distribution of these patterns in the source literatures.
    Appears in Collections:[資訊傳播學系] 科技部研究計畫

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