Kihara Daisuke, Yang Yifeng David, Hawkins Troy
Department of Biological Sciences, Department of Computer Science, Markey Center for StructuralBiology, The Bindley Bioscience Center, College of Science, Purdue University, West Lafayette, IN,47907, USA.
Cancer Inform. 2007 Feb 7;2:25-35.
The immensely popular fields of cancer research and bioinformatics overlap in many different areas, e.g. large data repositories that allow for users to analyze data from many experiments (data handling, databases), pattern mining, microarray data analysis, and interpretation of proteomics data. There are many newly available resources in these areas that may be unfamiliar to most cancer researchers wanting to incorporate bioinformatics tools and analyses into their work, and also to bioinformaticians looking for real data to develop and test algorithms. This review reveals the interdependence of cancer research and bioinformatics, and highlight the most appropriate and useful resources available to cancer researchers. These include not only public databases, but general and specific bioinformatics tools which can be useful to the cancer researcher. The primary foci are function and structure prediction tools of protein genes. The result is a useful reference to cancer researchers and bioinformaticians studying cancer alike.
广受欢迎的癌症研究领域和生物信息学在许多不同领域相互重叠,例如允许用户分析来自众多实验数据的大型数据库(数据处理、数据库)、模式挖掘、微阵列数据分析以及蛋白质组学数据解读。在这些领域有许多新的可用资源,大多数希望将生物信息学工具和分析纳入其工作的癌症研究人员以及寻求真实数据来开发和测试算法的生物信息学家可能对此并不熟悉。本综述揭示了癌症研究与生物信息学的相互依存关系,并着重介绍了癌症研究人员可获得的最合适且有用的资源。这些资源不仅包括公共数据库,还包括对癌症研究人员可能有用的通用和特定生物信息学工具。主要重点是蛋白质基因的功能和结构预测工具。其结果对于研究癌症的癌症研究人员和生物信息学家而言都是一份有用的参考资料。