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CC BY-NC-ND 4.0 · Yearb Med Inform 2021; 30(01): 219-225
DOI: 10.1055/s-0041-1726540
Section 8: Bioinformatics and Translational Informatics
Survey

Predictions, Pivots, and a Pandemic: a Review of 2020's Top Translational Bioinformatics Publications

Scott P. McGrath
1   CITRIS Health, University of California Berkeley, Berkeley, CA, USA
,
Mary Lauren Benton
2   Department of Computer Science, Baylor University, Waco, TX, USA
,
Maryam Tavakoli
3   MTERMS Lab, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
,
Nicholas P. Tatonetti
4   Department of Biomedical Informatics, Columbia University, New York, NY, USA
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Summary

Objectives: Provide an overview of the emerging themes and notable papers which were published in 2020 in the field of Bioinformatics and Translational Informatics (BTI) for the International Medical Informatics Association Yearbook.

Methods: A team of 16 individuals scanned the literature from the past year. Using a scoring rubric, papers were evaluated on their novelty, importance, and objective quality. 1,224 Medical Subject Headings (MeSH) terms extracted from these papers were used to identify themes and research focuses. The authors then used the scoring results to select notable papers and trends presented in this manuscript.

Results: The search phase identified 263 potential papers and central themes of coronavirus disease 2019 (COVID-19), machine learning, and bioinformatics were examined in greater detail.

Conclusions: When addressing a once in a centruy pandemic, scientists worldwide answered the call, with informaticians playing a critical role. Productivity and innovations reached new heights in both TBI and science, but significant research gaps remain.

Keywords

COVID-19 - machine learning - bioinformatics


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Artikel online veröffentlicht:
03. September 2021

© 2021. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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