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AnABlast: Re-searching for Protein-Coding Sequences in Genomic Regions

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Gene Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1962))

Abstract

AnABlast is a computational tool that highlights protein-coding regions within intergenic and intronic DNA sequences which escape detection by standard gene prediction algorithms. DNA sequences with small protein-coding genes or exons, complex intron-containing genes, or degenerated DNA fragments are efficiently targeted by AnABlast. Furthermore, this algorithm is particularly useful in detecting protein-coding sequences with nonsignificant homologs to sequences in databases. AnABlast can be executed online at http://www.bioinfocabd.upo.es/anablast/.

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Author information

Authors and Affiliations

  1. Facultad de Ciencias Experimentales (Área de Genética), Centro Andaluz de Biología del Desarrollo (CABD, UPO-CSIC), Universidad Pablo de Olavide, Sevilla, Spain

    Alejandro Rubio, Carlos S. Casimiro-Soriguer, Andrés Garzón, Juan Jimenez & Antonio J. Pérez-Pulido

  2. Faculty of Biology, Johannes Gutenberg University Mainz, Mainz, Germany

    Pablo Mier & Miguel A. Andrade-Navarro

Authors
  1. Alejandro Rubio
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  2. Carlos S. Casimiro-Soriguer
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  3. Pablo Mier
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  4. Miguel A. Andrade-Navarro
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  5. Andrés Garzón
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  6. Juan Jimenez
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  7. Antonio J. Pérez-Pulido
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Corresponding authors

Correspondence to Juan Jimenez or Antonio J. Pérez-Pulido .

Editor information

Editors and Affiliations

  1. Group Systems Biology of Motor Proteins, Department NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Goettingen, Germany

    Martin Kollmar

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Rubio, A. et al. (2019). AnABlast: Re-searching for Protein-Coding Sequences in Genomic Regions. In: Kollmar, M. (eds) Gene Prediction. Methods in Molecular Biology, vol 1962. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9173-0_12

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  • DOI: https://doi.org/10.1007/978-1-4939-9173-0_12

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9172-3

  • Online ISBN: 978-1-4939-9173-0

  • eBook Packages: Springer Protocols

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