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生物信息学:生命科学与个性化医学中的新工具及应用

Bioinformatics: new tools and applications in life science and personalized medicine.

作者信息

Branco Iuliia, Choupina Altino

机构信息

Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253, Bragança, Portugal.

出版信息

Appl Microbiol Biotechnol. 2021 Feb;105(3):937-951. doi: 10.1007/s00253-020-11056-2. Epub 2021 Jan 6.

DOI:10.1007/s00253-020-11056-2
PMID:33404829
Abstract

While we have a basic understanding of the functioning of the gene when coding sequences of specific proteins, we feel the lack of information on the role that DNA has on specific diseases or functions of thousands of proteins that are produced. Bioinformatics combines the methods used in the collection, storage, identification, analysis, and correlation of this huge and complex information. All this work produces an "ocean" of information that can only be "sailed" with the help of computerized methods. The goal is to provide scientists with the right means to explain normal biological processes, dysfunctions of these processes which give rise to disease and approaches that allow the discovery of new medical cures. Recently, sequencing platforms, a large scale of genomes and transcriptomes, have created new challenges not only to the genomics but especially for bioinformatics. The intent of this article is to compile a list of tools and information resources used by scientists to treat information from the massive sequencing of recent platforms to new generations and the applications of this information in different areas of life sciences including medicine. KEY POINTS: • Biological data mining • Omic approaches • From genotype to phenotype.

摘要

虽然我们对基因在编码特定蛋白质时的功能有了基本了解,但我们感到缺乏关于DNA在特定疾病或所产生的数千种蛋白质的特定功能方面所起作用的信息。生物信息学结合了用于收集、存储、识别、分析和关联这些庞大而复杂信息的方法。所有这些工作产生了一个“信息海洋”,只有借助计算机化方法才能“航行”。目标是为科学家提供正确的手段,以解释正常的生物过程、这些过程中导致疾病的功能障碍以及有助于发现新医学疗法的方法。最近,测序平台、大规模的基因组和转录组不仅给基因组学带来了新挑战,尤其是给生物信息学带来了新挑战。本文的目的是汇编一份科学家用于处理来自新一代最新平台大规模测序信息的工具和信息资源清单,以及这些信息在包括医学在内的生命科学不同领域的应用。要点:• 生物数据挖掘 • 组学方法 • 从基因型到表型

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