{
  "_id": "6a1c0da91d7bb097a0a2dc08",
  "Package": "planttfhunter",
  "Title": "Identification and classification of plant transcription factors",
  "Version": "1.13.0",
  "Date": "2022-03-10",
  "Authors@R": "c(\nperson(given = \"Fabrício\",\nfamily = \"Almeida-Silva\",\nrole = c(\"aut\", \"cre\"),\nemail = \"fabricio_almeidasilva@hotmail.com\",\ncomment = c(ORCID = \"0000-0002-5314-2964\")),\nperson(given = \"Yves\",\nfamily = \"Van de Peer\",\nrole = \"aut\",\nemail = \"yves.vandepeer@psb.vib-ugent.be\",\ncomment = c(ORCID = \"0000-0003-4327-3730\"))\n)",
  "Description": "planttfhunter is used to identify plant transcription\nfactors (TFs) from protein sequence data and classify them into\nfamilies and subfamilies using the classification scheme\nimplemented in PlantTFDB. TFs are identified using pre-built\nhidden Markov model profiles for DNA-binding domains. Then,\nauxiliary and forbidden domains are used with DNA-binding\ndomains to classify TFs into families and subfamilies (when\napplicable). Currently, TFs can be classified in 58 different\nTF families/subfamilies.",
  "License": "GPL-3",
  "URL": "https://github.com/almeidasilvaf/planttfhunter",
  "BugReports": "https://support.bioconductor.org/t/planttfhunter",
  "biocViews": "Software, Transcription, FunctionalPrediction,\nGenomeAnnotation, FunctionalGenomics, HiddenMarkovModel,\nSequencing, Classification",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:59:30 UTC",
  "RemoteUrl": "https://github.com/bioc/planttfhunter",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
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    "User": "root"
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  "Author": "Fabrício Almeida-Silva [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-5314-2964>),\nYves Van de Peer [aut] (ORCID: <https://orcid.org/0000-0003-4327-3730>)",
  "Maintainer": "Fabrício Almeida-Silva <fabricio_almeidasilva@hotmail.com>",
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  "_published": "2026-05-31T10:30:01.764Z",
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    "description": "Bioinformatics. Network biology. Plant genomics and evolution. #rstats addict.",
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    "transcription",
    "functionalprediction",
    "genomeannotation",
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    "hiddenmarkovmodel",
    "sequencing",
    "classification",
    "functional-genomics",
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