A text-mining analysis of the human phenome
A text-mining analysis of the human phenome
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DOI：
10.1038/sj.ejhg.5201585
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发表时间：
2006-05-01
影响因子：
5.2
通讯作者：
Leunissen, JA
中科院分区：
文献类型：
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作者：
van Driel, MA;Bruggeman, J;Leunissen, JA
许多大规模的努力正在进行中，以确定不同物种中基因和蛋白质之间的关系。但是，很少有人尝试在表型水平上对所有这些关系进行系统分类。此外，尚不清楚这种表型图谱是否携带有生物学意义的信息。我们已经使用文本挖掘分类超过5000个人类表型包含在在线孟德尔遗传在人数据库。我们发现表型之间的相似性反映了相互作用的功能相关基因的生物学模块。这些相似性与许多基因功能测量呈正相关，包括蛋白质序列水平上的亲缘关系、蛋白质基序、功能注释和直接的蛋白质-蛋白质相互作用。表型分组反映了人类疾病遗传学的模块化本质。因此，表型定位可用于预测疾病的候选基因以及基因和蛋白质之间的功能关系。如果开发出统一的表型描述符系统，这种预测将进一步改善。表型相似性数据可通过http://www.cmbi.ru.nl/MimMiner/的web界面访问。
A number of large-scale efforts are underway to define the relationships between genes and proteins in various species. But, few attempts have been made to systematically classify all such relationships at the phenotype level. Also, it is unknown whether such a phenotype map would carry biologically meaningful information. We have used text mining to classify over 5000 human phenotypes contained in the Online Mendelian Inheritance in Man database. We find that similarity between phenotypes reflects biological modules of interacting functionally related genes. These similarities are positively correlated with a number of measures of gene function, including relatedness at the level of protein sequence, protein motifs, functional annotation, and direct protein-protein interaction. Phenotype grouping reflects the modular nature of human disease genetics. Thus, phenotype mapping may be used to predict candidate genes for diseases as well as functional relations between genes and proteins. Such predictions will further improve if a unified system of phenotype descriptors is developed. The phenotype similarity data are accessible through a web interface at http://www.cmbi.ru.nl/MimMiner/.