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Contributions from the 2019 Literature on Bioinformatics and Translational Informatics

Objectives : Summarize recent research and select the best papers published in 2019 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association Yearbook. Methods : A literature review was performed for retrievi...

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Autores principales: Smaïl-Tabbone, Malika, Rance, Bastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442509/
https://www.ncbi.nlm.nih.gov/pubmed/32823315
http://dx.doi.org/10.1055/s-0040-1702002
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author Smaïl-Tabbone, Malika
Rance, Bastien
author_facet Smaïl-Tabbone, Malika
Rance, Bastien
author_sort Smaïl-Tabbone, Malika
collection PubMed
description Objectives : Summarize recent research and select the best papers published in 2019 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association Yearbook. Methods : A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the section editors to select a list of 15 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole Yearbook editorial committee was organized to finally decide on the selection of the best papers. Results : Among the 931 retrieved papers covering the various subareas of BTI, the review process selected four best papers. The first paper presents a logical modeling of cancer pathways. Using their tools, the authors are able to identify two known behaviours of tumors. The second paper describes a deep-learning approach to predicting resistance to antibiotics in Mycobacterium tuberculosis. The authors of the third paper introduce a Genomic Global Positioning System (GPS) enabling comparison of genomic data with other individuals or genomics databases while preserving privacy. The fourth paper presents a multi-omics and temporal sequence-based approach to provide a better understanding of the sequence of events leading to Alzheimer’s Disease. Conclusions : Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.
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spelling pubmed-74425092020-08-24 Contributions from the 2019 Literature on Bioinformatics and Translational Informatics Smaïl-Tabbone, Malika Rance, Bastien Yearb Med Inform Objectives : Summarize recent research and select the best papers published in 2019 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association Yearbook. Methods : A literature review was performed for retrieving from PubMed papers indexed with keywords and free terms related to BTI. Independent review allowed the section editors to select a list of 15 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole Yearbook editorial committee was organized to finally decide on the selection of the best papers. Results : Among the 931 retrieved papers covering the various subareas of BTI, the review process selected four best papers. The first paper presents a logical modeling of cancer pathways. Using their tools, the authors are able to identify two known behaviours of tumors. The second paper describes a deep-learning approach to predicting resistance to antibiotics in Mycobacterium tuberculosis. The authors of the third paper introduce a Genomic Global Positioning System (GPS) enabling comparison of genomic data with other individuals or genomics databases while preserving privacy. The fourth paper presents a multi-omics and temporal sequence-based approach to provide a better understanding of the sequence of events leading to Alzheimer’s Disease. Conclusions : Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine. Georg Thieme Verlag KG 2020-08 2020-08-21 /pmc/articles/PMC7442509/ /pubmed/32823315 http://dx.doi.org/10.1055/s-0040-1702002 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Smaïl-Tabbone, Malika
Rance, Bastien
Contributions from the 2019 Literature on Bioinformatics and Translational Informatics
title Contributions from the 2019 Literature on Bioinformatics and Translational Informatics
title_full Contributions from the 2019 Literature on Bioinformatics and Translational Informatics
title_fullStr Contributions from the 2019 Literature on Bioinformatics and Translational Informatics
title_full_unstemmed Contributions from the 2019 Literature on Bioinformatics and Translational Informatics
title_short Contributions from the 2019 Literature on Bioinformatics and Translational Informatics
title_sort contributions from the 2019 literature on bioinformatics and translational informatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442509/
https://www.ncbi.nlm.nih.gov/pubmed/32823315
http://dx.doi.org/10.1055/s-0040-1702002
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