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Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review)
The development of high-throughput technologies has sharply increased the opportunities to research the human body at the molecular, cellular, and organismal levels in the last decade. Rapid progress in biotechnology has caused a paradigm shift in population-based studies. Advances in modern biomedi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Privolzhsky Research Medical University
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10171044/ https://www.ncbi.nlm.nih.gov/pubmed/37179982 http://dx.doi.org/10.17691/stm2022.14.4.07 |
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author | Denisov, N.S. Kamenskikh, E.M. Fedorova, O.S. |
author_facet | Denisov, N.S. Kamenskikh, E.M. Fedorova, O.S. |
author_sort | Denisov, N.S. |
collection | PubMed |
description | The development of high-throughput technologies has sharply increased the opportunities to research the human body at the molecular, cellular, and organismal levels in the last decade. Rapid progress in biotechnology has caused a paradigm shift in population-based studies. Advances in modern biomedical sciences, including genomic, genome-wide, post-genomic research and bioinformatics, have contributed to the emergence of molecular epidemiology focused on the study of the personalized molecular mechanism of disease development and its extrapolation to the population level. The work of research teams at the intersection of information technology and medicine has become the basis for highlighting digital epidemiology, the important tools of which are machine learning, the ability to work with real world data, and accumulated big data. The developed approaches accelerate the process of collecting and processing biomedical data, testing new scientific hypotheses. However, new methods are still in their infancy, they require testing of application under various conditions, as well as standardization. This review highlights the role of omics and digital technologies in population-based studies. |
format | Online Article Text |
id | pubmed-10171044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Privolzhsky Research Medical University |
record_format | MEDLINE/PubMed |
spelling | pubmed-101710442023-05-11 Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) Denisov, N.S. Kamenskikh, E.M. Fedorova, O.S. Sovrem Tekhnologii Med Reviews The development of high-throughput technologies has sharply increased the opportunities to research the human body at the molecular, cellular, and organismal levels in the last decade. Rapid progress in biotechnology has caused a paradigm shift in population-based studies. Advances in modern biomedical sciences, including genomic, genome-wide, post-genomic research and bioinformatics, have contributed to the emergence of molecular epidemiology focused on the study of the personalized molecular mechanism of disease development and its extrapolation to the population level. The work of research teams at the intersection of information technology and medicine has become the basis for highlighting digital epidemiology, the important tools of which are machine learning, the ability to work with real world data, and accumulated big data. The developed approaches accelerate the process of collecting and processing biomedical data, testing new scientific hypotheses. However, new methods are still in their infancy, they require testing of application under various conditions, as well as standardization. This review highlights the role of omics and digital technologies in population-based studies. Privolzhsky Research Medical University 2022 2022-07-29 /pmc/articles/PMC10171044/ /pubmed/37179982 http://dx.doi.org/10.17691/stm2022.14.4.07 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Reviews Denisov, N.S. Kamenskikh, E.M. Fedorova, O.S. Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) |
title | Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) |
title_full | Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) |
title_fullStr | Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) |
title_full_unstemmed | Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) |
title_short | Trends in Population-Based Studies: Molecular and Digital Epidemiology (Review) |
title_sort | trends in population-based studies: molecular and digital epidemiology (review) |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10171044/ https://www.ncbi.nlm.nih.gov/pubmed/37179982 http://dx.doi.org/10.17691/stm2022.14.4.07 |
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