MedMeSH Summarizer: Text Mining for Gene Clusters
MedMeSH Summarizer: Text Mining for Gene Clusters
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DOI：
10.1137/1.9781611972726.32
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
P. Kankar;S. Adak;A. Sarkar;K. Murali;Gaurav Sharma
中科院分区：
文献类型：
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作者：
P. Kankar;S. Adak;A. Sarkar;K. Murali;Gaurav Sharma
基因表达是将基因编码信息翻译成细胞中存在和运作的蛋白质的过程。基因表达的变化与许多重要的生物学现象有关，包括形态发生和衰老、癌症和疾病状态以及对环境的适应性反应。高密度微阵列的出现，介绍了Schena等人。[1]在1995年，第一次有可能同时测量给定基因组中所有或大多数基因的表达水平。从那时起，cDNA微阵列[2]和基因芯片（也称为高密度寡核苷酸阵列）[6]已被广泛用于在不同环境条件下生成不同生物体的全基因组表达谱。用于全基因组表达谱分析的微阵列技术是新的且快速发展的，我们请读者参考最近的综述（[4]，[3]，[5]）。使用这些微阵列生成的大量数据为研究人员提供了一个重要的机会，可以使用系统的计算方法来改变生物学，医学和药理学。全基因组表达谱的可用性有望对理解基本细胞过程、疾病的诊断和治疗以及设计和提供靶向治疗的功效产生深远影响。与这些目标特别相关的是将实验和分析结果与先前已知的生物学事实，理论和结果交叉引用的能力。生物和医学文献数据库提供了这种广泛的交叉引用所需的知识仓库。然而，此类数据库的数量使得交叉引用的任务非常冗长、乏味和令人生畏。本文中描述的MedMeSH Summarizer系统正是为了帮助生物学家交叉引用从微阵列实验中获得的实验和分析结果而设计的。
Gene Expression is the process by which a gene’s coded information is translated into the proteins present and operating in the cell. Changes in gene expression are associated with many important biological phenomena, including morphogenesis and aging, cancer and disease states, and adaptive responses to the environment. The advent of high density microarrays, introduced by Schena et al.[1] in 1995, made it possible for the first time to measure the expression levels simultaneously of all or most of the genes in a given genome. Since then, cDNA microarrays[2] and GeneChips (also called high-density oligonucleotide arrays)[6] have been used extensively in generating genome-wide expression profiles for different organisms under different environmental conditions. The microarray technologies for whole-genome expression profiling are new and rapidly evolving, and we refer the reader to the recent reviews ([4],[3],[5]). The vast quantity of data being generated using these microarrays provides researchers with a significant opportunity to transform biology, medicine, and pharmacology using systematic computational methods. The availability of genome-wide expression profiles promises to have a profound impact on the understanding of basic cellular processes, the diagnosis and treatment of disease, and the efficacy of designing and delivering targeted therapeutics. Particularly relevant to these objectives is the ability to cross-reference experimental and analytical results with previously known biological facts, theories, and results. Biological and medical literature databases provide the kind of knowledge warehouses required for such extensive crossreferencing. However, the volume of such databases makes the task of cross-referencing very lengthy, tedious, and daunting. The MedMeSH Summarizer system described in this paper is geared precisely for this task of helping a biologist in cross-referencing experimental and analytical results obtained from microarray experiments.