Evidence map›Paper›PMID 33816556›Full record

ArticleFrontiers in molecular biosciences2021

Low Diversity of Human Variation Despite Mostly Mild Functional Impact of De Novo Variants.

Yannick Mahlich, Maximillian Miller, Zishuo Zeng, Yana Bromberg

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Decoding the effects of synonymous variants.Nucleic acids research · 2021
    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

4 authors at 1 institution in 1 country.

Yannick MahlichDepartment of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, United States.
Maximillian MillerDepartment of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, United States.
Zishuo ZengDepartment of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, United States.
Yana BrombergDepartment of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, United States.
Rutgers, The State University of New Jersey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-synonymous Single Nucleotide Variants (nsSNVs), resulting in single amino acid variants (SAVs), are important drivers of evolutionary adaptation across the tree of life. Humans carry on average over 10,000 SAVs per individual genome, many of which likely have little to no impact on the function of the protein they affect. Experimental evidence for protein function changes as a result of SAVs remain sparse - a situation that can be somewhat alleviated by predicting their impact using computational methods. Here, we used SNAP to examine both

Indexed as

adaptationcommon variationcross-species variationevolutionnsSNVsSNAPvariation

Identifiers

PMID33816556
PMCPMC8012514
OpenAlexW3139206820

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.