Evidence map›Paper›PMID 25495442›Full record

ArticleBMC genomics2014

Categorizer: a tool to categorize genes into user-defined biological groups based on semantic similarity.

Dokyun Na, Hyungbin Son, Jörg Gsponer

Abstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

18 citing papers in PubMed.

  1. Article
  2. Native Wound-Repair Proteins Retained in Multilayer Placental CAMPs.International journal of molecular sciences · 2025
    Article
  3. Slimformer: An NLP-based web server for semantic categorization of gene sets.Computational and structural biotechnology journal · 2025
    Article
  4. Article
  5. GCN2 is required to maintain core body temperature in mice during acute cold.American journal of physiology. Endocrinology and metabolism · 2023
    Article
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  15. In-Cardiome: integrated knowledgebase for coronary artery disease enabling translational research.Database : the journal of biological databases and curation · 2017
    Article
  16. Article
  17. 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

3 authors.

Dokyun Na
Hyungbin Son
Jörg GsponerDepartment of Biochemistry and Molecular Biology, Centre for High-throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, BC V6T 1Z4, Canada. gsponer@chibi.ubc.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommunalities between large sets of genes obtained from high-throughput experiments are often identified by searching for enrichments of genes with the same Gene Ontology (GO) annotations. The GO analysis tools used for these enrichment analyses assume that GO terms are independent and the semantic distances between all parent-child terms are identical, which is not true in a biological sense. In addition these tools output lists of often redundant or too specific GO terms, which are difficult to interpret in the context of the biological question investigated by the user. Therefore, there is a demand for a robust and reliable method for gene categorization and enrichment analysis.

resultsWe have developed Categorizer, a tool that classifies genes into user-defined groups (categories) and calculates p-values for the enrichment of the categories. Categorizer identifies the biologically best-fit category for each gene by taking advantage of a specialized semantic similarity measure for GO terms. We demonstrate that Categorizer provides improved categorization and enrichment results of genetic modifiers of Huntington's disease compared to a classical GO Slim-based approach or categorizations using other semantic similarity measures.

conclusionCategorizer enables more accurate categorizations of genes than currently available methods. This new tool will help experimental and computational biologists analyzing genomic and proteomic data according to their specific needs in a more reliable manner.

Indexed as

SoftwareComputational BiologyDatabases, GeneticHumansHuntington DiseaseMolecular Sequence AnnotationUser-Computer Interface

Identifiers

PMID25495442
PMCPMC4298957

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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.