van Driel Marc A, Brunner Han G
Molecular Biology Department, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.
Hum Genomics. 2006 Jun;2(6):429-32. doi: 10.1186/1479-7364-2-6-429.
With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information is the usual strategy by which candidate disease genes are selected. Enrichment for candidate disease genes, however, depends on the skills of the operating researcher. Over the past few years, a number of bioinformatics methods that enrich for the most likely candidate disease genes have been developed. Such in silico prioritisation methods may further improve by completion of datasets, by development of standardised ontologies across databases and species and, ultimately, by the integration of different strategies.
随着基因组学和功能基因组学信息的激增,疾病基因识别方法正在迅速发展。数据库现在对于选择候选疾病基因的过程至关重要。将定位信息与疾病特征和功能信息相结合是选择候选疾病基因的常用策略。然而,候选疾病基因的富集取决于操作研究人员的技能。在过去几年中,已经开发了许多能够富集最有可能的候选疾病基因的生物信息学方法。通过完善数据集、开发跨数据库和物种的标准化本体,以及最终整合不同策略,这种计算机优先排序方法可能会进一步改进。