Towards precision medicine: advances in computational approaches for the analysis of human variants.
Towards precision medicine: advances in computational approaches for the analysis of human variants.
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DOI：
10.1016/j.jmb.2013.08.008
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发表时间：
2013-11-01
影响因子：
5.6
通讯作者：
Kann, Maricel G.
中科院分区：
文献类型：
--
作者：
Peterson, Thomas A.;Doughty, Emily;Kann, Maricel G.
我们个体基因组的差异和相似性是我们历史、遗产和身份的一部分。一些人类基因组变异与头发和眼睛颜色等共同特征有关，而另一些则与疾病易感性或对药物治疗的反应有关。识别产生临床相关表型变化的人类变异对于提供准确和个性化的疾病诊断、预后和治疗至关重要。此外，更好地了解疾病的分子基础可以为精准医疗开发新的药物靶点。已经设计了一些资源，用于在高度结构化、易于访问的数据库中收集和存储人类基因组变异。不幸的是，关于这些遗传变异及其功能和表型关联的大量信息目前被埋没在文献中，只能通过人工管理或复杂的文本挖掘技术来提取相关信息。此外，低成本的测序技术加上不断提高的计算能力，使得许多计算方法的发展能够预测人类变异的致病性。这篇综述提供了当前人类变异资源的详细比较，包括HGMD、OMIM、ClinVar和UniProt/Swiss-Prot，随后概述了用于利用现有数据预测新的有害变异的计算方法和技术。我们希望这些资源和工具能够成为理解导致疾病的基因组变异的分子细节的基础，从而实现精准医学的承诺。
Variations and similarities in our individual genomes are part of our history, our heritage, and our identity. Some human genomic variants are associated with common traits such as hair and eye color, while others are associated with susceptibility to disease or response to drug treatment. Identifying the human variations producing clinically relevant phenotypic changes is critical for providing accurate and personalized diagnosis, prognosis, and treatment for diseases. Furthermore, a better understanding of the molecular underpinning of disease can lead to development of new drug targets for precision medicine. Several resources have been designed for collecting and storing human genomic variations in highly structured, easily accessible databases. Unfortunately, a vast amount of information about these genetic variants and their functional and phenotypic associations is currently buried in the literature, only accessible by manual curation or sophisticated text mining technology to extract the relevant information. In addition, the low cost of sequencing technologies coupled with increasing computational power has enabled the development of numerous computational methodologies to predict the pathogenicity of human variants. This review provides a detailed comparison of current human variant resources, including HGMD, OMIM, ClinVar, and UniProt/Swiss-Prot, followed by an overview of the computational methods and techniques used to leverage the available data to predict novel deleterious variants. We expect these resources and tools to become the foundation for understanding the molecular details of genomic variants leading to disease, which in turn will enable the promise of precision medicine.
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影响因子：
3.9
作者：
Amberger, Joanna;Bocchini, Carol;Hamosh, Ada
通讯作者：
Hamosh, Ada
影响因子：
5.9
作者：
Baker, CJO;Witte, R
通讯作者：
Witte, R
影响因子：
168.9
作者：
Ashley, Euan A.;Butte, Atul J.;Wheeler, Matthew T.;Chen, Rong;Klein, Teri E.;Dewey, Frederick E.;Dudley, Joel T.;Ormond, Kelly E.;Pavlovic, Aleksandra;Morgan, Alexander A.;Pushkarev, Dmitry;Neff, Norma F.;Hudgins, Louanne;Gong, Li;Hodges, Laura M.;Berlin, Dorit S.;Thorn, Caroline F.;Sangkuhl, Katrin;Hebert, Joan M.;Woon, Mark;Sagreiya, Hersh;Whaley, Ryan;Knowles, Joshua W.;Chou, Michael F.;Thakuria, Joseph V.;Rosenbaum, Abraham M.;Zaranek, Alexander Wait;Church, George M.;Greely, Henry T.;Quake, Stephen R.;Altman, Russ B.
通讯作者：
Altman, Russ B.
影响因子：
14.9
作者：
Bao L;Zhou M;Cui Y
通讯作者：
Cui Y
DOI：
10.1038/nrg2918
发表时间：
2011-01
期刊：
Nature reviews. Genetics
影响因子：
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作者：
通讯作者：
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