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通过分子数据和大规模“深度”生物信息学分析详细阐述衰老科学的生物医学方面。

Detailing the biomedical aspects of geroscience by molecular data and large-scale "deep" bioinformatics analyses.

机构信息

Clinic for Cardiac Surgery, University Medicine of the Martin-Luther-University Halle-Wittenberg, Ernst-Grube Str. 40, 06120, Halle (Saale), Germany.

Institute for Biostatistics and Informatics in Medicine and Ageing Research -- IBIMA, Rostock University Medical Center, Ernst-Heydemann-Str. 8, 18057, Rostock, Germany.

出版信息

Z Gerontol Geriatr. 2024 Aug;57(5):355-360. doi: 10.1007/s00391-024-02329-w. Epub 2024 Aug 1.

Abstract

As scientists investigated the molecular mechanisms of the biology of aging, they discovered that these are malleable and can enhance healthy longevity by intervening in the drivers of aging, which are leading to disease, dysfunction and death. These exciting observations gave birth to the field of geroscience. As the mechanisms of aging affect almost all mechanisms of life, detailed molecular mechanistic knowledge must be gained or expanded by considering and integrating as many types of data as possible, from genes and transcripts to socioenvironmental factors. Such a large-scale integration of large amounts of data will in turn profit from "deep" bioinformatics analyses that provide insights beyond contextualizing and interpreting the data in the light of knowledge from databases such as the Gene Ontology. The authors suggest that "deep" bioinformatics, employing methods based on artificial intelligence, will be a key ingredient of future analyses.

摘要

随着科学家研究衰老生物学的分子机制,他们发现这些机制是可塑的,可以通过干预导致疾病、功能障碍和死亡的衰老驱动因素来增强健康长寿。这些令人兴奋的观察结果催生了衰老科学领域。由于衰老的机制几乎影响到生命的所有机制,因此必须通过考虑和整合尽可能多类型的数据来获得或扩展详细的分子机制知识,这些数据类型从基因和转录本到社会环境因素都有涉及。这种大规模的大量数据的整合反过来也将受益于“深度”生物信息学分析,这些分析提供了超越基于数据库(如基因本体论)知识来语境化和解释数据的见解。作者建议,基于人工智能的“深度”生物信息学方法将成为未来分析的一个关键要素。

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