Srinivasan Padmini, Libbus Bisharah
School of Library and Information Science, University of Iowa, Iowa City, IA 52242, USA.
Bioinformatics. 2004 Aug 4;20 Suppl 1:i290-6. doi: 10.1093/bioinformatics/bth914.
Text mining systems aim at knowledge discovery from text collections. This work presents our text mining algorithm and demonstrates its use to uncover information that could form the basis of new hypotheses. In particular, we use it to discover novel uses for Curcuma longa, a dietary substance, which is highly regarded for its therapeutic properties in Asia.
Several disease were identified that offer novel research contexts for curcumin. We analyze select suggestions, such as retinal diseases, Crohn's disease and disorders related to the spinal cord. Our analysis suggests that there is strong evidence in favor of a beneficial role for curcumin in these diseases. The evidence is based on curcumin's influence on several genes, such as COX-2, TNF-alpha, JNK, p38 MAPK and TGF-beta. This research suggests that our discovery algorithm may be used to suggest novel uses for dietary and pharmacological substances. More generally, our text mining algorithm may be used to uncover information that potentially sheds new light on a given topic of interest.
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文本挖掘系统旨在从文本集合中发现知识。这项工作展示了我们的文本挖掘算法，并演示了其用于揭示可能构成新假设基础的信息的用途。特别是，我们用它来发现姜黄（一种在亚洲因其治疗特性而备受推崇的食用物质）的新用途。
确定了几种疾病，为姜黄素提供了新的研究背景。我们分析了一些选定的建议，如视网膜疾病、克罗恩病和与脊髓相关的疾病。我们的分析表明，有强有力的证据支持姜黄素在这些疾病中发挥有益作用。该证据基于姜黄素对几种基因的影响，如COX - 2、TNF - α、JNK、p38 MAPK和TGF - β。这项研究表明，我们的发现算法可用于为食用和药理物质提出新用途。更一般地说，我们的文本挖掘算法可用于揭示可能为给定感兴趣主题带来新启示的信息。
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