Evidence map›Paper›PMID 38956207›Full record

ArticleNature genetics2024

Improving transparency of computational tools for variant effect prediction.

Rachel Karchin, Predrag Radivojac, Anne O'Donnell-Luria, Marc S Greenblatt, Michael Y Tolstorukov, Dmitriy Sonkin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Review
  4. Best Practices for Machine Learning-Assisted Protein Engineering.Journal of chemical information and modeling · 2025
    Review
  5. Article
  6. Article
  7. Article
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

6 authors.

Rachel KarchinThe Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, USA. karchin@jhu.edu.ORCID http://orcid.org/0000-0002-5069-1239
Predrag RadivojacKhoury College of Computer Sciences, Northeastern University, Boston, MA, USA.ORCID http://orcid.org/0000-0002-6769-0793
Anne O'Donnell-LuriaProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-6418-9592
Marc S GreenblattDepartment of Medicine and University of Vermont Cancer Center, University of Vermont, Larner College of Medicine, Burlington, VT, USA.
Michael Y TolstorukovDepartment of Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA, USA.ORCID http://orcid.org/0000-0002-9134-8808
Dmitriy SonkinNational Cancer Institute, Division of Cancer Treatment and Diagnosis, Rockville, MD, USA. dmitriy.sonkin@nih.gov.ORCID http://orcid.org/0000-0002-1649-0652

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Computational BiologyGenetic VariationHumansSoftware

Identifiers

PMID38956207
PMCPMC11330584

What OpenQuestion holds

Textmetadata
LicenceTDM
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.