Evidence map›Paper›PMID 32823315›Full record

ReviewYearbook of medical informatics2020

Contributions from the 2019 Literature on Bioinformatics and Translational Informatics.

Malika Smaïl-Tabbone, Bastien Rance, Section Editors for the IMIA Yearbook Section on Bioinformatics and Translational Informatics

Abstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. High-throughput proteomics: a methodological mini-review.Laboratory investigation; a journal of technical methods and pathology · 2022
    Review
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Malika Smaïl-TabboneLoria UMR 7503, Université de Lorraine, CNRS, Inria Nancy Grand-Est, Nancy, France.
Bastien RanceHEGP, AP-HP & Université de Paris, UMRS 1138 Centre de Recherche des Cordeliers, INSERM, Paris, France.
Section Editors for the IMIA Yearbook Section on Bioinformatics and Translational Informatics

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSummarize 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.

methodsA 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.

resultsAmong 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.

conclusionsThanks 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.

Indexed as

Computational BiologyGenomicsHumansMachine LearningMedical InformaticsTranslational Research, Biomedical

Identifiers

PMID32823315
PMCPMC7442509

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.