Dauchel H, Lecroq T. Findings from the Section on Bioinformatics and Translational Informatics.
Yearb Med Inform 2016:188-192. [PMID:
27830252 DOI:
10.15265/iy-2016-050]
[Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES
To summarize excellent current research and propose a selection of best papers published in 2015 in the field of Bioinformatics and Translational Informatics with application in the health domain and clinical care.
METHOD
We provide a synopsis of the articles selected for the IMIA Yearbook 2016, from which we attempt to derive a synthetic overview of current and future activities in the field. As last year, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section. Each section editor has evaluated separately the set of 1,566 articles and the evaluation results were merged for retaining 14 articles for peer-review.
RESULTS
The selection and evaluation process of this Yearbook's section on Bioinformatics and Translational Informatics yielded four excellent articles focusing this year on data management of large-scale datasets and genomic medicine that are mainly new method-based papers. Three articles explore the high potential of the re-analysis of previously collected data, here from The Cancer Genome Atlas project (TCGA) and one article presents an original analysis of genomic data from sub-Saharan Africa populations.
CONCLUSIONS
The current research activities in Bioinformatics and Translational Informatics with application in the health domain continues to explore new algorithms and statistical models to manage and interpret large-scale genomic datasets. From population wide genome sequencing for cataloging genomic variants to the comprehension of functional impact on pathways and molecular interactions regarding a given pathology, making sense of large genomic data requires a necessary effort to address the issue of clinical translation for precise diagnostic and personalized medicine.
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