The indigenous populations as the model by nature to understand human genomic-phenomics interactions
Background: The advancement of genomics has progressed in lightning speed over the past two decades. Numerous large-scale genome sequencing initiatives were announced, along with the rise of the holistic precision medicine approach. However, the field of genomic medicine has now come to a bottleneck...
Published in: | Quantitative Biology |
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Higher Education Press Limited Company
2022
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2-s2.0-85128206534 Hoh B.-P.; Rahman T.A. The indigenous populations as the model by nature to understand human genomic-phenomics interactions 2022 Quantitative Biology 10 1 10.15302/J-QB-021-0251 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128206534&doi=10.15302%2fJ-QB-021-0251&partnerID=40&md5=ddd6b75bb58077db5f09c2af6ea220b5 Background: The advancement of genomics has progressed in lightning speed over the past two decades. Numerous large-scale genome sequencing initiatives were announced, along with the rise of the holistic precision medicine approach. However, the field of genomic medicine has now come to a bottleneck since genomic-phenomic interactions are not fully comprehended due to the complexity of the human systems biology and environmental influence, hence the emergence of human phenomics. Results: This review attempts to provide an overview of the potential advantages of investigating the human phenomics of indigenous populations and the challenges ahead. Conclusion: We believe that the indigenous populations serve as an ideal model to excavate our understanding of genomic-environmental-phenomics interactions. © The Author(s) 2021. Published by Higher Education Press. Higher Education Press Limited Company 20954689 English Review All Open Access; Gold Open Access |
author |
Hoh B.-P.; Rahman T.A. |
spellingShingle |
Hoh B.-P.; Rahman T.A. The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
author_facet |
Hoh B.-P.; Rahman T.A. |
author_sort |
Hoh B.-P.; Rahman T.A. |
title |
The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
title_short |
The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
title_full |
The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
title_fullStr |
The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
title_full_unstemmed |
The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
title_sort |
The indigenous populations as the model by nature to understand human genomic-phenomics interactions |
publishDate |
2022 |
container_title |
Quantitative Biology |
container_volume |
10 |
container_issue |
1 |
doi_str_mv |
10.15302/J-QB-021-0251 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128206534&doi=10.15302%2fJ-QB-021-0251&partnerID=40&md5=ddd6b75bb58077db5f09c2af6ea220b5 |
description |
Background: The advancement of genomics has progressed in lightning speed over the past two decades. Numerous large-scale genome sequencing initiatives were announced, along with the rise of the holistic precision medicine approach. However, the field of genomic medicine has now come to a bottleneck since genomic-phenomic interactions are not fully comprehended due to the complexity of the human systems biology and environmental influence, hence the emergence of human phenomics. Results: This review attempts to provide an overview of the potential advantages of investigating the human phenomics of indigenous populations and the challenges ahead. Conclusion: We believe that the indigenous populations serve as an ideal model to excavate our understanding of genomic-environmental-phenomics interactions. © The Author(s) 2021. Published by Higher Education Press. |
publisher |
Higher Education Press Limited Company |
issn |
20954689 |
language |
English |
format |
Review |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809678158059798528 |