Evotec (UK) limited, 114 Milton Park, Abingdon, Oxfordshire, OX14 4SA, UK.
Curr Top Med Chem. 2012;12(18):1965-79. doi: 10.2174/156802612804910331.
Technological advances in high-throughput screening methods, combinatorial chemistry and the design of virtual libraries have evolved in the pursuit of challenging drug targets. Over the last two decades a vast amount of data has been generated within these fields and as a consequence data mining methods have been developed to extract key pieces of information from these large data pools. Much of this data is now available in the public domain. This has been helpful in the arena of drug discovery for both academic groups and for small to medium sized enterprises which previously would not have had access to such data resources. Commercial data mining software is sometimes prohibitively expensive and the alternate open source data mining software is gaining momentum in both academia and in industrial applications as the costs of research and development continue to rise. KNIME, the Konstanz Information Miner, has emerged as a leader in open source data mining tools. KNIME provides an integrated solution for the data mining requirements across the drug discovery pipeline through a visual assembly of data workflows drawing from an extensive repository of tools. This review will examine KNIME as an open source data mining tool and its applications in drug discovery.
在高通量筛选方法、组合化学和虚拟库设计方面的技术进步，是为了追求具有挑战性的药物靶点而发展起来的。在过去的二十年中，这些领域产生了大量的数据，因此开发了数据挖掘方法来从这些大型数据集中提取关键信息。现在，其中的大部分数据都可以公开获得。这对学术团体和中小型企业来说都在药物发现领域都很有帮助，因为这些企业以前无法获得这样的数据资源。商业数据挖掘软件有时价格过高，而开源数据挖掘软件则在学术界和工业应用中逐渐流行起来，因为研发成本持续上升。KNIME，即康斯坦茨信息矿工，已成为开源数据挖掘工具的领导者。KNIME 通过从广泛的工具库中提取数据工作流程的可视化组装，为药物发现管道中的数据挖掘需求提供了一个集成的解决方案。本文将考察 KNIME 作为一个开源的数据挖掘工具及其在药物发现中的应用。
