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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "ttgsea" in publications use:'
type: software
license: Artistic-2.0
title: 'ttgsea: Tokenizing Text of Gene Set Enrichment Analysis'
version: 1.13.0
doi: 10.32614/CRAN.package.ttgsea
abstract: Functional enrichment analysis methods such as gene set enrichment analysis
  (GSEA) have been widely used for analyzing gene expression data. GSEA is a powerful
  method to infer results of gene expression data at a level of gene sets by calculating
  enrichment scores for predefined sets of genes. GSEA depends on the availability
  and accuracy of gene sets. There are overlaps between terms of gene sets or categories
  because multiple terms may exist for a single biological process, and it can thus
  lead to redundancy within enriched terms. In other words, the sets of related terms
  are overlapping. Using deep learning, this pakage is aimed to predict enrichment
  scores for unique tokens or words from text in names of gene sets to resolve this
  overlapping set issue. Furthermore, we can coin a new term by combining tokens and
  find its enrichment score by predicting such a combined tokens.
authors:
- family-names: Jung
  given-names: Dongmin
  email: dmdmjung@gmail.com
  orcid: https://orcid.org/0000-0001-7499-8422
repository: https://bioc.r-universe.dev
commit: 23e12ac0890c9c9faa925f4fd584483534a7db5f
date-released: '2021-11-12'
contact:
- family-names: Jung
  given-names: Dongmin
  email: dmdmjung@gmail.com
  orcid: https://orcid.org/0000-0001-7499-8422