用計算機網(wǎng)絡和數(shù)據(jù)庫收集、組織和分析大量的生物數(shù)據(jù)。歷史上生物信息學涉及基因序列和其產(chǎn)物蛋白質(zhì)的分析，但是該領域已經(jīng)擴展到從基因組學、蛋白組學、藥物篩選和藥物化學中獲得的大量資料的管理、處理、分析和形象化。 生物信息學還包括對從這些學科中得到的不斷膨脹的數(shù)據(jù)庫的整合與挖掘。一個企業(yè)范圍的生物信息學方法包括一個內(nèi)部數(shù)據(jù)庫系統(tǒng)，與外界數(shù)據(jù)庫的輸入與連接，中間層面軟件向研究者描述感興趣的生物研究對象，演繹層面提供分析和研究工具，用戶層面使用者可以以各種方式接近、整合、操作和看到數(shù)據(jù)。

The collection, organization and analysis of large amounts of biological data, using networks of computers and databases. Historically, bioinformatics concerned itself with the analysis of the sequences of genes and their products (proteins), but the field has since expanded to the management, processing, analysis and visualization of large quantities of data from genomics, proteomics, drug screening and medicinal chemistry. Bioinformatics also includes the integration and “mining” (detailed searching) of the ever-expanding databases of information from these disciplines. An enterprise wide bioinformatics solution includes an internal database system, feeds and links to external (public, collaborative) databases, a middle tier of software that defines the biological objects of interest to the researcher, an algorithm tier where the analysis and mining tools reside, and a user tier where the user can access, integrate, manipulate and visualize the data in a variety of ways.