Evidence map›Paper›PMID 27051459›Full record

ArticleComputational and mathematical methods in medicine2016

Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides.

Wojciech Wieczorek, Olgierd Unold

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2016. 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
–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

1 citing paper in PubMed.

  1. RFAmyloid: A Web Server for Predicting Amyloid Proteins.International journal of molecular sciences · 2018
    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

2 authors.

Wojciech WieczorekFaculty of Computer Science and Materials Science, University of Silesia, Ulica Zytnia 12, 41-200 Sosnowiec, Poland.ORCID 0000-0003-3191-9151
Olgierd UnoldDepartment of Computer Engineering, Faculty of Electronics, Wroclaw University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370 Wroclaw, Poland.ORCID 0000-0003-4722-176X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present paper is a novel contribution to the field of bioinformatics by using grammatical inference in the analysis of data. We developed an algorithm for generating star-free regular expressions which turned out to be good recommendation tools, as they are characterized by a relatively high correlation coefficient between the observed and predicted binary classifications. The experiments have been performed for three datasets of amyloidogenic hexapeptides, and our results are compared with those obtained using the graph approaches, the current state-of-the-art methods in heuristic automata induction, and the support vector machine. The results showed the superior performance of the new grammatical inference algorithm on fixed-length amyloid datasets.

Indexed as

Computational BiologyAlgorithmsAmyloidAutomationDatabases, FactualFalse Positive ReactionsHumansLanguageModels, BiologicalModels, StatisticalPeptidesReproducibility of ResultsSensitivity and SpecificitySupport Vector MachineAmyloidPeptides

Identifiers

PMID27051459
PMCPMC4804041

What OpenQuestion holds

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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.