生物信息学(来自Bioinformatics)利用应用数学、信息学、统计学和计算机科学的方法研究生物学的问题。生物信息学基本上只360百科是分子生物学与信息技术(尤其是因特网技术)的结合体。生物信息学的研究材料和结果就是各种各样的生物学数据，其研究座顶星密印立第工具是计算机，研究方法包括对生物学数据的搜索(收集和筛选)、处理(编辑、整理、管理和显示)及利用(计算、模拟)。主要的研究方向有:序列比对，基因识别，基因重组，蛋白质结构预测，基因表达，蛋白质反应的预测，理怀棉损虽益元以及建立进化论的模型。

• 中文名称 生物信息学
• 外文名称 bioinformatics
• 定义 利用数学的方法研究生物学的问题
• 主要研究方向 序列比对，基因识别等

含义

　　生物学技术往往生成大量的嘈杂数据。与数据挖掘类似，生物信息白啊静愿罗法振极价既广学利用数学工具从大量数据中提取有用的生物学花领散信息。生物信息学所要处理的典型问题包括:重新组装在波早绝皮实谈状霰弹枪定序法测序过程中被打散的DNA序列，从蛋白质的氨基酸序列预测蛋白质结构，利用mRNA微阵列或质谱仪的数据检验基因调控的假说。

　　某些人将计算生物学作为生物信息学的同义词处理，在英语维基获外啊阶质百科中就是如此;但是另外一些人认为计算生物学和生物信息学预载探应当被当作不同的条目处理，因为生物信息学更侧重于台始元够止帮销么环深末生物学领域中计算方法的使用和发展，而计算生物学强调应用信息学技术对生物学领域中的假说进行检验，并尝试发展新的理论。

英文对照

　　The terms bioinformatics and computational biology are ofte字考春吗光她n used interchangeably. However bioinformatics m来自ore properly refers to the creatio360百科n and advancement of algorithms, computational and statistical techniques, and theory to solve formal and pr面号京底督控滑转actical prob待剂让治经京推教风lems inspired from the management and analysis of biological data. Computational biology, on the other hand, refers to hypothesis-driven investigation of a specific biological pr粮oblem 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 concerne怀民顺耐优跳器喜d with the information while com较走料胶居他衡丰防游难putational biology is con决鱼cerned with the hypothes调款具低好结es. A similar distinction is made by National Instit害势主特每赶口沙财待滑utes of Health in their working definitions of Bioinformatics and C延绿己银统史坐胶额omputational Biology, where it is further 考看呼较养喜江否emphasized that there is a tight 吧斤总丰妈区曲旧困突略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.