bioinformatics

生物學技術往往生成大量的嘈雜數據。與數據挖掘類似，生物信息學利用數學工具從大量數據中提取有用的生物學信息。生物信息學所要處理的典型問題包括：重新組裝在霰彈槍定序法測序過程中被打散的DNA序列，從蛋白質的氨基酸序列預測蛋白質結構，利用mRNA微陣列或質譜儀的數據檢驗基因調控的假説。

某些人將計算生物學作為生物信息學的同義詞處理，在英語維基百科中就是如此；但是另外一些人認為計算生物學和生物信息學應當被當作不同的條目處理，因為生物信息學更側重於生物學領域中計算方法的使用和發展，而計算生物學強調應用信息學技術對生物學領域中的假説進行檢驗，並嘗試發展新的理論。

The terms bioinformatics and computational biology are often used interchangeably. However bioinformatics more properly refers to the creation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems inspired from the management and analysis of biological data. Computational biology, on the other hand, refers to hypothesis-driven investigation of a specific biological problem using computers, carried out with experimental or simulated data, with the primary goal of discovery and the advancement of biological knowledge. Put more simply, bioinformatics is concerned with the information while computational biology is concerned with the hypotheses. A similar distinction is made by National Institutes of Health in their working definitions of Bioinformatics and Computational Biology, where it is further emphasized that there is a tight coupling of developments and knowledge between the more hypothesis-driven research in computational biology and technique-driven research in bioinformatics.

A common thread in projects in bioinformatics and computational biology is the use of mathematical tools to extract useful information from data produced by high-throughput biological techniques such as genome sequencing. A representative problem in bioinformatics is the assembly of high-quality genome sequences from fragmentary "shotgun" DNA sequencing. Other common problems include the study of gene regulation using data from microarrays or mass spectrometry.