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Contributions from the 2018 Literature on Bioinformatics and Translational Informatics
- Source :
- IMIA Yearbook of Medical Informatics, IMIA Yearbook of Medical Informatics, Schattauer, 2019, 28 (01), pp.190-193. ⟨10.1055/s-0039-1677945⟩, Yearbook of Medical Informatics, IMIA Yearbook of Medical Informatics, 2019, 28 (01), pp.190-193. ⟨10.1055/s-0039-1677945⟩
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- Objectives: To summarize recent research and select the best papers published in 2018 in the field of Bioinformatics and Translational Informatics (BTI) for the corresponding section of the International Medical Informatics Association (IMIA) 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 two section editors to select a list of 14 candidate best papers which were subsequently peer-reviewed. A final consensus meeting gathering the whole IMIA Yearbook editorial committee was organized to finally decide on the selection of the best papers. Results: Among the 636 retrieved papers published in 2018 in the various subareas of BTI, the review process selected four best papers. The first paper presents a computational method to identify molecular markers for targeted treatment of acute myeloid leukemia using multi-omics data (genome-wide gene expression profiles) and in vitro sensitivity to 160 chemotherapy drugs. The second paper describes a deep neural network approach to predict the survival of patients suffering from glioma on the basis of digitalised pathology images and genomics biomarkers. The authors of the third paper adopt a pan-cancer approach to take benefit of multi-omics data for drug repurposing. The fourth paper presents a graph-based semi-supervised method to accurate phenotype classification applied to ovarian cancer. 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.
- Subjects :
- Open science
020205 medical informatics
Computer science
International Medical Informatics Association Yearbook
MEDLINE
02 engineering and technology
Bioinformatics
Health informatics
Field (computer science)
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Machine Learning
Translational Research, Biomedical
03 medical and health sciences
0302 clinical medicine
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
Artificial Intelligence
Neoplasms
0202 electrical engineering, electronic engineering, information engineering
bioinformatics and translational informatics
Humans
Translational research informatics
030212 general & internal medicine
ComputingMilieux_MISCELLANEOUS
Section 8: Bioinformatics and Translational Informatics
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]
business.industry
Computational Biology
General Medicine
Prognosis
3. Good health
Open data
ComputingMethodologies_PATTERNRECOGNITION
Synopsis
Yearbook
Personalized medicine
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
business
Medical Informatics
Subjects
Details
- Language :
- English
- ISSN :
- 09434747, 23640502, and 00261270
- Database :
- OpenAIRE
- Journal :
- IMIA Yearbook of Medical Informatics, IMIA Yearbook of Medical Informatics, Schattauer, 2019, 28 (01), pp.190-193. ⟨10.1055/s-0039-1677945⟩, Yearbook of Medical Informatics, IMIA Yearbook of Medical Informatics, 2019, 28 (01), pp.190-193. ⟨10.1055/s-0039-1677945⟩
- Accession number :
- edsair.doi.dedup.....f2f24a92e93505dab7e9de706c367efa