School of Computing, National University of Singapore, Building COM1, 117417 Singapore.
BMC Bioinformatics. 2010 Sep 7;11:449. doi: 10.1186/1471-2105-11-449.
It is necessary to analyze microarray experiments together with biological information to make better biological inferences. We investigate the adequacy of current biological databases to address this need.
Our results show a low level of consistency, comprehensiveness and compatibility among three popular pathway databases (KEGG, Ingenuity and Wikipathways). The level of consistency for genes in similar pathways across databases ranges from 0% to 88%. The corresponding level of consistency for interacting genes pairs is 0%-61%. These three original sources can be assumed to be reliable in the sense that the interacting gene pairs reported in them are correct because they are curated. However, the lack of concordance between these databases suggests each source has missed out many genes and interacting gene pairs.
Researchers will hence find it challenging to obtain consistent pathway information out of these diverse data sources. It is therefore critical to enable them to access these sources via a consistent, comprehensive and unified pathway API. We accumulated sufficient data to create such an aggregated resource with the convenience of an API to access its information. This unified resource can be accessed at http://www.pathwayapi.com.
有必要结合生物信息来分析微阵列实验，以做出更好的生物学推论。我们研究了当前生物数据库是否足以满足这一需求。
我们的研究结果表明，三个流行的通路数据库（KEGG、Ingenuity 和 Wikipathways）在一致性、全面性和兼容性方面的水平较低。数据库中相似通路的基因一致性水平范围为 0%至 88%。相互作用基因对的相应一致性水平为 0%-61%。这三个原始来源可以被认为是可靠的，因为它们所报告的相互作用基因对是经过精心整理的，所以是正确的。然而，这些数据库之间缺乏一致性表明，每个来源都遗漏了许多基因和相互作用基因对。
研究人员将发现很难从这些不同的数据源中获得一致的通路信息。因此，通过一致、全面和统一的通路 API 使他们能够访问这些资源是至关重要的。我们积累了足够的数据来创建这样一个聚合资源，并通过 API 方便地访问其信息。这个统一的资源可以在 http://www.pathwayapi.com 上访问。
