Evidence map›Paper›PMID 28293637›Full record

ArticleBioMed research international2017

Identification of Candidate Genes Related to Inflammatory Bowel Disease Using Minimum Redundancy Maximum Relevance, Incremental Feature Selection, and the Shortest-Path Approach.

Fei Yuan, Yu-Hang Zhang, Xiang-Yin Kong, Yu-Dong Cai

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

21 citing papers in PubMed, 32 citations in OpenAlex.

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  15. Artificial Intelligence Enhances Studies on Inflammatory Bowel Disease.Frontiers in bioengineering and biotechnology · 2021
    Review
  16. An initial genome-wide investigation of protein-losing enteropathy in Gordon setters: Exploratory observations.Canadian journal of veterinary research = Revue canadienne de recherche veterinaire · 2021
    Article
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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 3 institutions in 1 country.

Fei YuanDepartment of Science & Technology, Binzhou Medical University Hospital, Binzhou 256603, Shandong, China.ORCID 0000-0002-9681-6367
Yu-Hang ZhangInstitute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Xiang-Yin KongInstitute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Yu-Dong CaiSchool of Life Sciences, Shanghai University, Shanghai 200444, China.ORCID 0000-0001-5664-7979
Chinese Academy of Sciences · CNBinzhou Medical University · CNShanghai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of disease genes is a hot topic in biomedicine and genomics. However, it is a challenging problem because of the complexity of diseases. Inflammatory bowel disease (IBD) is an idiopathic disease caused by a dysregulated immune response to host intestinal microflora. It has been proven to be associated with the development of intestinal malignancies. Although the specific pathological characteristics and genetic background of IBD have been partially revealed, it is still an overdetermined disease and the blueprint of all genetic variants still needs to be improved. In this study, a novel computational method was built to identify genes related to IBD. Samples from two subtypes of IBD (ulcerative colitis and Crohn's disease) and normal samples were employed. By analyzing the gene expression profiles of these samples using minimum redundancy maximum relevance and incremental feature selection, 21 genes were obtained that could effectively distinguish samples from the two subtypes of IBD and the normal samples. Then, the shortest-path approach was used to search for an additional 20 genes in a large network constructed using protein-protein interactions based on the above-mentioned 21 genes. Analyses of the 41 genes obtained indicate that they are closely associated with this disease.

Indexed as

Genetic Predisposition to DiseaseComputational BiologyDatabases, GeneticGene Expression ProfilingGenetic VariationGenome, HumanGenomicsHumansInflammatory Bowel DiseasesIntestinal NeoplasmsOligonucleotide Array Sequence AnalysisProtein Interaction MappingSignal TransductionSupport Vector Machine

Identifiers

PMID28293637
PMCPMC5331171
OpenAlexW2588920758

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.