黃乾綱臺灣大學:工程科學及海洋工程學研究所黃俊欽Huang, Chun-ChinChun-ChinHuang2010-07-142018-06-282010-07-142018-06-282009U0001-1208200922061900http://ntur.lib.ntu.edu.tw//handle/246246/188998蛋白質和DNA的交互作用通常牽涉到DNA的轉錄、複製、遺傳訊息傳送、或是基因重組等重要生化作用。而蛋白質與DNA的結合特性又可分為序列專一性結合以及非專一性結合。序列專一性結合能夠去辨識特定的DNA鹼基對部份；另一方面，非專一性結合主要是與DNA的醣基-磷酸部份進行反應。論文第一階段在討論結合殘基預測。對具序列專一性結合殘基的預測，分類預測器能夠達到96.45%的精確度、50.14%的靈敏度、99.31%的專一性、以及81.70%的準確度和高達62.15%的F型測量值；而非專一性結合預測器可達到89.14%的精確度、53.06%的靈敏度、95.25%的專一性、以及65.47%的準確性和高達58.62%的F型測量值。此外，我們將兩項預測結果進行OR運算後，可獲得89.26%的精確度、56.86%的靈敏度、95.63%的專一性、以及71.92%的準確性和63.51%的F型測量值。論文第二階段則探討蛋白質-DNA結合模式的預測，所設計的多類型分類的支援向量機可達到75.83%的精確度。論文研究呈現了以序列資訊為基礎的預測分類器，且該分類器能夠針對與DNA結合機制有關的轉錄因子，預測序列專一性結合殘基以及非專一性結合殘基。而發展蛋白質-DNA結合型態的預測器，其目標是希望能夠提供生化學者額外的結構預測資訊，並進一步提升殘基的預測表現。此外，我們也從本實驗中學習相關經驗，將經驗應用在轉錄因子以外的蛋白質類型的結合性殘基預測。Protein-DNA interactions are essential for fundamental biochemical activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two modes distinguished by sequence-specific and non-specific binding respectively. Protein-DNA specific binding provides a mechanism to recognize correct nucleotide base pairs namely sequence-specific identification. On the other hand, protein-DNA non-specific binding shows relatively little base-sequence preference and interacts with DNA backbone.n this thesis, we present a two stage Protein-DNA binding prediction. In the first stage of DNA-binding residues prediction, the predictor for DNA specific binding residues achieves 96.45% accuracy with 50.14% sensitivity, 99.31% specificity, 81.70% precision, and 62.15% F-measure. The predictor for DNA non-specific binding residues achieves 89.14% accuracy with 53.06% sensitivity, 95.25% specificity, 65.47% precision, and 58.62% F-measure. In addition, we combine the results of sequence-specific and non-specific binding residues predicted in previous stage with OR operation, and the predictor achieves 89.26% accuracy with 56.86% sensitivity, 95.63% specificity, 71.92% precision, and 63.51% F-measure. In the second stage, a protein-DNA interaction mode predictor is proposed. It can achieve 75.83% accuracy while using support vector machine with multi-class prediction.his article presents the design of a sequence-based predictor aiming to identify the sequence-specific and non-specific DNA-binding residues in a transcription factor with DNA binding-mechanism concerned. The protein-DNA interaction mode prediction was introduced to provide biochemist more structural hint and help improve previous DNA-binding residues prediction. In addition, we will exploit the experiences learned in this study to design binding-mechanism concerned predictors for other types of DNA-contacted proteins.誌謝 i要 iiBSTRACT iii有名詞對照 v錄 vi目錄 viii目錄 xhapter1 導論 1hapter2 相關工作 5.1 專一性結合與非專一性結合 5.2 預測方法之相關文獻探討 8.3 資料集合 (Dataset) 的取得 10.4 定義結合性殘基 12.5 定義蛋白質-DNA結合型態 13.6 分類器套件—LIBSVM 18.7 其它工具及專有名詞 21hapter3 實驗方法 25.1 實驗架構與分類器 25.2 特徵選取與向量編碼 27.3 資料正規化處理 30.4 驗證方法 30.5 獨立測試 31hapter4 實驗結果與討論 34.1 最佳參數選取 34.2 表現評估 34hapter5 結論 49獻參考 53錄 581856387 bytesapplication/pdfen-US結合性殘基預測序列專一性結合非專一性結合支援向量機轉錄因子DNA-binding residues predictionsequence-specific bindingnon-specific bindingsupport vector machinetranscription factorthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/188998/1/ntu-98-R96525072-1.pdf