Evidence map›Paper›PMID 31271472›Full record

ArticleProtein science : a publication of the Protein Society2019

ProtDCal-Suite: A web server for the numerical codification and functional analysis of proteins.

Sandra Romero-Molina, Yasser B Ruiz-Blanco, James R Green, Elsa Sanchez-Garcia

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  5. Machine Learning Methods in Protein-Protein Docking.Methods in molecular biology (Clifton, N.J.) · 2024
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  15. Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.International journal of molecular sciences · 2020
    Article
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  17. 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.

Sandra Romero-MolinaComputational Biochemistry, Center of Medical Biotechnology, University of Duisburg-Essen, Essen, Germany.
Yasser B Ruiz-BlancoComputational Biochemistry, Center of Medical Biotechnology, University of Duisburg-Essen, Essen, Germany.ORCID 0000-0001-5400-4427
James R GreenSystems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada.ORCID 0000-0002-6039-2355
Elsa Sanchez-GarciaComputational Biochemistry, Center of Medical Biotechnology, University of Duisburg-Essen, Essen, Germany.ORCID 0000-0002-9211-5803

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational tools for the analysis of protein data and the prediction of biological properties are essential in life sciences and biomedical research. Here, we introduce ProtDCal-Suite, a web server comprising a set of machine learning-based methods for studying proteins. The main module of ProtDCal-Suite is the ProtDCal software. ProtDCal translates the structural information of proteins into numerical descriptors that serve as input to machine-learning techniques. The ProtDCal-Suite server also incorporates a post-processing optional stage that allows ranking and filtering the obtained descriptors by computing their Shannon entropy values across the input set of proteins. ProtDCal's codification was used in the development of models for the prediction of specific protein properties. Thus, the other modules of ProtDCal-Suite are protein analysis tools implemented using ProtDCal's descriptors. Among them are PPI-Detect, for predicting the interaction likelihood of protein-protein and protein-peptide pairs, Enzyme Identifier, for identifying enzymes from amino acid sequences or 3D structures, and Pred-NGlyco, for predicting N-glycosylation sites. ProtDCal-Suite is freely accessible at https://protdcal.zmb.uni-due.de.

Indexed as

Computational BiologyDatabases, ProteinInternetMachine LearningModels, MolecularProteinsProteinsdescriptorenzymesmachine-learningN-glycosylationprotein-protein interactionsweb server

Identifiers

PMID31271472
PMCPMC6699089

What OpenQuestion holds

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Registered trials

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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.