臺灣博碩士論文加值系統

生物資訊結合了數學、化學、統計、分子生物學及電腦等多門學科來研究生命科學，為現代分子生物學的主流；生物資訊的功能在於如何呈現、儲存及傳播資料。資料挖掘是在龐大的資料中搜尋資料，存成資料庫，從中發現以前未注意到有趣而且有用的資訊。生物資訊提供機會發展各種資料挖掘的方法，因此從大型序列資料庫中發現序列、結構及模型的過程裡，資料挖掘將扮演越來越吃重的角色。
美國國家生物科技資訊中心（NCBI）提供了一個大規模的資訊系統來支援未來科學資訊上的需求；它的任務即是發展新的技術，幫助了解那些控制健康和疾病的分子和遺傳基因。
本篇論文除了介紹美國國家生物科技資訊中心裡的文獻資料庫，也對於資料挖掘的任務及相關技術做詳盡的介紹；同時列舉幾種在美國國家生物科技資訊中心裡常用的資料挖掘的工具，也介紹這些工具的特性和基本的操作方法。目的即是探討資料挖掘技術應用在生物資訊上所發展出來的新興領域，進而了解資料挖掘在生物資訊領域裡所呈現無限潛能的應用與發展。

Bioinformatics represents a new, growing area of science that computational approaches to answer biological questions. With the explosion of sequence and structural information available to researchers, the field of bioinformatics is playing an increasingly large role in the study of fundamental biomedical problems.

The functional view of bioinformatics is the representation, storage, and distribution of data. Data mining is used to refer the process of searching through a large volume of data, stored into a database, to discover interesting and useful information previously unknown. Bioinformatics provides opportunities for developing different data mining methods. Data mining will play an increasingly important role in the analysis and discovery of sequence, structure and functional patterns or models from large sequence databases.

NCBI provides large-scale informatics systems that will support scientific inquiry well into the future. The mission of the NCBI is to develop new information technologies to aid in the understanding of fundamental molecular and genetic processes that control health and disease.

In this thesis, we enumerate several kinds of data mining tools often used inside NCBI. We also introduce the characteristics of these tools and basic operation methods . So we can understand the data mining application and development of limitless latent energy appeared in bioinformatics field.

中文摘要 …………………………………………………………………… i
英文摘要 …………………………………………………………………… ii
誌謝 …………………………………………………………………… iv
目錄 …………………………………………………………………… v
第一章 簡介 ……………………………………………………………… 1
1.1 生物資訊 …………………………………………………… 1
1.2 資料挖掘 …………………………………………………………… 1
1.3 資料挖掘在生物資訊的應用………………………………………… 2
第二章 資料挖掘工具 ……………………………………………………… 4
2.1 資料挖掘過程 …………………………………………………… 4
2.2 資料挖掘的任務 ………………………………………………… 6
2.3 資料挖掘的相關技術 ……………………………………………… 12
第三章 生物資訊的常見資料 ……………………………………………… 15
3.1 GenBank ……………………………………………………… 15
3.2 分子生物資料庫 …………………………………………………… 21
3.3 文獻資料庫 ………………………………………………………… 23
第四章 NCBI的資料挖掘工具 …………………………………………… 34
4.1 BLAST …………………………………………………………… 34
4.2 COGs ……………………………………………………………… 37
4.3 Map Viewer ……………………………………………………… 39
4.4 LocusLink ………………………………………………………… 41
4.5 UniGene …………………………………………………………… 44
4.6 CGAP ……………………………………………………………… 45
第五章 結論 ……………………………………………………………… 47
參考文獻 …………………………………………………………………… 48

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