更新时间:2022-07-01 21:52
生物信息学(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,以及建立进化论的模型。
生物学技术往往生成大量的嘈杂数据。与数据挖掘类似,生物信息学利用数学工具从大量数据中提取有用的生物学信息。生物信息学所要处理的典型问题包括:重新组装在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应当被当作不同的条目处理,因为生物信息学更侧重于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。
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.