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...
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28 years and 1 months (reg. 1997-05-29).

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Keywords {🔍}

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Topics {✒️}

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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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         type:WebPageElement
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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:
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