Evidence map›Paper›PMID 35992603›Full record

ArticleFrontiers in aging neuroscience2022

Machine-learning analysis of intrinsically disordered proteins identifies key factors that contribute to neurodegeneration-related aggregation.

Akshatha Ganne, Meenakshisundaram Balasubramaniam, Srinivas Ayyadevara, Robert J Shmookler Reis

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2022. 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
1.1field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Chaotic aging: intrinsically disordered proteins in aging-related processes.Cellular and molecular life sciences : CMLS · 2023
    Article
  6. 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 2 institutions in 1 country.

Akshatha GanneBioinformatics Program, University of Arkansas for Medical Sciences and University of Arkansas at Little Rock, Little Rock, AR, United States.
Meenakshisundaram BalasubramaniamDepartment of Geriatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Srinivas AyyadevaraBioinformatics Program, University of Arkansas for Medical Sciences and University of Arkansas at Little Rock, Little Rock, AR, United States.
Robert J Shmookler ReisBioinformatics Program, University of Arkansas for Medical Sciences and University of Arkansas at Little Rock, Little Rock, AR, United States.
University of Arkansas for Medical Sciences · USCentral Arkansas Veterans Healthcare System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein structure is determined by the amino acid sequence and a variety of post-translational modifications, and provides the basis for physiological properties. Not all proteins in the proteome attain a stable conformation; roughly one third of human proteins are unstructured or contain intrinsically disordered regions exceeding 40% of their length. Proteins comprising or containing extensive unstructured regions are termed intrinsically disordered proteins (IDPs). IDPs are known to be overrepresented in protein aggregates of diverse neurodegenerative diseases. We evaluated the importance of disordered proteins in the nematode

Indexed as

Alzheimer’s diseasedrug screening and discoveryintrinsically disordered proteins (IDPs)misfolding and aggregationneural networkParkinson’s diseaseproteostasissupport vector machine

Identifiers

PMID35992603
PMCPMC9382113
OpenAlexW4289516864

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.