Evidence map›Paper›PMID 32696351›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2020

Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor.

Christopher J Oldfield, Xiao Fan, Chen Wang, A Keith Dunker, Lukasz Kurgan

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Accurate and Fast Prediction of Intrinsic Disorder Using flDPnn.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  2. Deep learning in prediction of intrinsic disorder in proteins.Computational and structural biotechnology journal · 2022
    Review
  3. Predicting Protein Conformational Disorder and Disordered Binding Sites.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  4. 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

5 authors at 3 institutions in 1 country.

Christopher J OldfieldDepartment of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
Xiao FanDepartment of Pediatrics, Columbia University, New York, NY, USA.
Chen WangDepartment of Medicine, Columbia University, New York, NY, USA.
A Keith DunkerDepartment of Biochemistry and Molecular Biology, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
Lukasz KurganDepartment of Computer Science, Virginia Commonwealth University, Richmond, VA, USA. lkurgan@vcu.edu.
Columbia University · USVirginia Commonwealth University · USIndiana University – Purdue University Indianapolis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intrinsically disordered proteins are either entirely disordered or contain disordered regions in their native state. These proteins and regions function without the prerequisite of a stable structure and were found to be abundant across all kingdoms of life. Experimental annotation of disorder lags behind the rapidly growing number of sequenced proteins, motivating the development of computational methods that predict disorder in protein sequences. DisCoP is a user-friendly webserver that provides accurate sequence-based prediction of protein disorder. It relies on meta-architecture in which the outputs generated by multiple disorder predictors are combined together to improve predictive performance. The architecture of disCoP is presented, and its accuracy relative to several other disorder predictors is briefly discussed. We describe usage of the web interface and explain how to access and read results generated by this computational tool. We also provide an example of prediction results and interpretation. The disCoP's webserver is publicly available at http://biomine.cs.vcu.edu/servers/disCoP/ .

Indexed as

AlgorithmsAmino Acid SequenceComputational BiologyDNA-Binding ProteinsIntrinsically Disordered ProteinsDNA-Binding ProteinsIntrinsically Disordered ProteinsBioinformaticsIDPIntrinsically disordered proteinsMeta-architectureWebserver

Identifiers

PMID32696351
OpenAlexW3045259969

What OpenQuestion holds

Textmetadata
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.