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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "GOSemSim" in publications use:'
type: software
license: Artistic-2.0
title: 'GOSemSim: GO-terms Semantic Similarity Measures'
version: 2.38.0
doi: 10.1007/978-1-0716-0301-7_11
identifiers:
- type: doi
  value: 10.32614/CRAN.package.GOSemSim
abstract: The semantic comparisons of Gene Ontology (GO) annotations provide quantitative
  ways to compute similarities between genes and gene groups, and have became important
  basis for many bioinformatics analysis approaches. GOSemSim is an R package for
  semantic similarity computation among GO terms, sets of GO terms, gene products
  and gene clusters. GOSemSim implemented five methods proposed by Resnik, Schlicker,
  Jiang, Lin and Wang respectively.
authors:
- family-names: Yu
  given-names: Guangchuang
  email: guangchuangyu@gmail.com
preferred-citation:
  type: article
  title: Gene Ontology Semantic Similarity Analysis Using GOSemSim
  authors:
  - family-names: Yu
    given-names: Guangchuang
    email: guangchuangyu@gmail.com
  journal: Methods in Molecular Biology
  year: '2020'
  volume: '2117'
  issn: 1940-6029
  doi: 10.1007/978-1-0716-0301-7_11
  start: 207-215
repository: https://bioc-release.r-universe.dev
repository-code: https://github.com/YuLab-SMU/GOSemSim
commit: 03895b5346c5ce198e58ce17c1fb87d9c719b7df
url: https://yulab-smu.top/biomedical-knowledge-mining-book/
date-released: '2026-04-28'
contact:
- family-names: Yu
  given-names: Guangchuang
  email: guangchuangyu@gmail.com
references:
- type: article
  title: 'GOSemSim: an R package for measuring semantic similarity among GO terms
    and gene products'
  authors:
  - family-names: Yu
    given-names: Guangchuang
  - family-names: Li
    given-names: Fei
  - family-names: Qin
    given-names: Yide
  - family-names: Bo
    given-names: Xiaochen
  - family-names: Wu
    given-names: Yibo
  - family-names: Wang
    given-names: Shengqi
  journal: Bioinformatics
  year: '2010'
  volume: '26'
  issue: '7'
  doi: 10.1093/bioinformatics/btq064
  start: 976-978