We are analyzing https://link.springer.com/protocol/10.1007/978-1-4939-9173-0_1.

Title:
tRNAscan-SE: Searching for tRNA Genes in Genomic Sequences | SpringerLink
Description:
Transfer RNAs are the largest, most complex non-coding RNA family, universal to all living organisms. tRNAscan-SE has been the de facto tool for predicting tRNA genes in whole genomes. The newly developed version 2.0 has incorporated advanced methodologies with...
Website Age:
28 years and 1 months (reg. 1997-05-29).

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Keywords {🔍}

article, google, scholar, cas, genes, search, protocol, lowe, rna, privacy, cookies, content, information, publish, trnascanse, chan, access, nucleic, acids, res, nature, springer, analysis, gene, trna, online, biology, transfer, genomes, chapter, sequence, lee, genome, download, personal, data, log, journal, research, prediction, genomic, sequences, todd, open, eddy, database, durbin, kollmar, author, ebook,

Topics {✒️}

month download article/chapter trna-ala anticodon mutations privacy choices/manage cookies nuclear codon reassignments device instant download online web versions transfer rna genes ultralow rna-seq genomic sequences protocol library preparation based ucsc genome browser editor information editors coding rna family lowe tm gene prediction european economic area de facto tool incorporated advanced methodologies unix command-driven d'souza lm jensen-seaman mi confer auxin resistance max-planck-institute journal finder publish conditions privacy policy predicting trna genes de jong pj short interspersed elements rna sequence analysis accepting optional cookies mammalian trna genes eddy sr california santa cruz springer nature gonzalez-garay ml main content log check access ethics access bmc genomics 12 rna-seq protocol usd 49 trnascan-se author correspondence protocol chan social media affiliations department permissions reprints chan pp protocol cite genomic sequences

Schema {🗺️}

ScholarlyArticle:
      headline:tRNAscan-SE: Searching for tRNA Genes in Genomic Sequences
      pageEnd:14
      pageStart:1
      image:https://media.springernature.com/w153/springer-static/cover/book/978-1-4939-9173-0.jpg
      genre:
         Springer Protocols
      isPartOf:
         name:Gene Prediction
         isbn:
            978-1-4939-9173-0
            978-1-4939-9172-3
         type:Book
      publisher:
         name:Springer New York
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:Patricia P. Chan
            affiliation:
                  name:University of California Santa Cruz
                  address:
                     name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Todd M. Lowe
            affiliation:
                  name:University of California Santa Cruz
                  address:
                     name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
      keywords:Transfer RNA, Non-coding RNA, Gene prediction, Covariance model, RNA secondary structure
      description:Transfer RNAs are the largest, most complex non-coding RNA family, universal to all living organisms. tRNAscan-SE has been the de facto tool for predicting tRNA genes in whole genomes. The newly developed version 2.0 has incorporated advanced methodologies with improved probabilistic search software and a suite of new gene models, enabling better functional classification of predicted genes. This chapter describes the use of the UNIX command-driven and online web versions, illustrating different search modes and options.
      datePublished:2019
      isAccessibleForFree:
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         cssSelector:.main-content
         type:WebPageElement
      context:https://schema.org
Book:
      name:Gene Prediction
      isbn:
         978-1-4939-9173-0
         978-1-4939-9172-3
Organization:
      name:Springer New York
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:University of California Santa Cruz
      address:
         name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
         type:PostalAddress
      name:University of California Santa Cruz
      address:
         name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
      name:Patricia P. Chan
      affiliation:
            name:University of California Santa Cruz
            address:
               name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
               type:PostalAddress
            type:Organization
      name:Todd M. Lowe
      affiliation:
            name:University of California Santa Cruz
            address:
               name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
      name:Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, USA
WebPageElement:
      isAccessibleForFree:
      cssSelector:.main-content

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