Translational Bioinformatics for Human Reproductive Biology Research: Examples, Opportunities and Challenges for a Future Reproductive Medicine
dc.contributor.author | Liu, Kun | |
dc.contributor.author | Zhang, Yingbo | |
dc.contributor.author | Martín Plágaro, César Augusto | |
dc.contributor.author | Ma, Xiaoling | |
dc.contributor.author | Shen, Bairong | |
dc.date.accessioned | 2023-01-12T15:12:46Z | |
dc.date.available | 2023-01-12T15:12:46Z | |
dc.date.issued | 2022-12-20 | |
dc.identifier.citation | International Journal of Molecular Sciences 24(1) : (2023) // Article ID 4 | es_ES |
dc.identifier.issn | 1422-0067 | |
dc.identifier.uri | http://hdl.handle.net/10810/59264 | |
dc.description.abstract | Since 1978, with the first IVF (in vitro fertilization) baby birth in Manchester (England), more than eight million IVF babies have been born throughout the world, and many new techniques and discoveries have emerged in reproductive medicine. To summarize the modern technology and progress in reproductive medicine, all scientific papers related to reproductive medicine, especially papers related to reproductive translational medicine, were fully searched, manually curated and reviewed. Results indicated whether male reproductive medicine or female reproductive medicine all have made significant progress, and their markers have experienced the progress from karyotype analysis to single-cell omics. However, due to the lack of comprehensive databases, especially databases collecting risk exposures, disease markers and models, prevention drugs and effective treatment methods, the application of the latest precision medicine technologies and methods in reproductive medicine is limited. | es_ES |
dc.description.sponsorship | This research was funded by Project of Natural Science Foundation of Gansu Province (20JR5RA363); Project of Gansu Provincial Education Department (2020B-003). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | reproductive medicine | es_ES |
dc.subject | translational bioinformatics | es_ES |
dc.subject | infertility | es_ES |
dc.subject | biomarkers | es_ES |
dc.subject | artificial intelligence | es_ES |
dc.subject | database | es_ES |
dc.subject | knowledge graph | es_ES |
dc.title | Translational Bioinformatics for Human Reproductive Biology Research: Examples, Opportunities and Challenges for a Future Reproductive Medicine | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2023-01-06T13:52:40Z | |
dc.rights.holder | © 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1422-0067/24/1/4 | es_ES |
dc.identifier.doi | 10.3390/ijms24010004 | |
dc.departamentoes | Bioquímica y biología molecular | |
dc.departamentoeu | Biokimika eta biologia molekularra |
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Except where otherwise noted, this item's license is described as © 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/).