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UniProtKB/Swiss-Prot中的基因变异与疾病:专家人工注释的来龙去脉

Genetic variations and diseases in UniProtKB/Swiss-Prot: the ins and outs of expert manual curation.

作者信息

Famiglietti Maria Livia, Estreicher Anne, Gos Arnaud, Bolleman Jerven, Géhant Sébastien, Breuza Lionel, Bridge Alan, Poux Sylvain, Redaschi Nicole, Bougueleret Lydie, Xenarios Ioannis

机构信息

Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland.

出版信息

Hum Mutat. 2014 Aug;35(8):927-35. doi: 10.1002/humu.22594. Epub 2014 Jun 24.

Abstract

During the last few years, next-generation sequencing (NGS) technologies have accelerated the detection of genetic variants resulting in the rapid discovery of new disease-associated genes. However, the wealth of variation data made available by NGS alone is not sufficient to understand the mechanisms underlying disease pathogenesis and manifestation. Multidisciplinary approaches combining sequence and clinical data with prior biological knowledge are needed to unravel the role of genetic variants in human health and disease. In this context, it is crucial that these data are linked, organized, and made readily available through reliable online resources. The Swiss-Prot section of the Universal Protein Knowledgebase (UniProtKB/Swiss-Prot) provides the scientific community with a collection of information on protein functions, interactions, biological pathways, as well as human genetic diseases and variants, all manually reviewed by experts. In this article, we present an overview of the information content of UniProtKB/Swiss-Prot to show how this knowledgebase can support researchers in the elucidation of the mechanisms leading from a molecular defect to a disease phenotype.

摘要

在过去几年中,新一代测序(NGS)技术加快了对基因变异的检测,从而迅速发现了新的疾病相关基因。然而,仅靠NGS提供的大量变异数据不足以理解疾病发病机制和表现背后的机制。需要将序列和临床数据与先前的生物学知识相结合的多学科方法,以阐明基因变异在人类健康和疾病中的作用。在这种情况下,至关重要的是,这些数据要通过可靠的在线资源进行链接、整理并随时可用。通用蛋白质知识库(UniProtKB/Swiss-Prot)的Swiss-Prot部分为科学界提供了关于蛋白质功能、相互作用、生物途径以及人类遗传疾病和变异的信息集合,所有这些都经过专家手动审核。在本文中,我们概述了UniProtKB/Swiss-Prot的信息内容,以展示该知识库如何支持研究人员阐明从分子缺陷到疾病表型的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7754/4285303/45cc68d25f12/humu0035-0927-f1.jpg

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