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Computational Methods for Ab Initio and Comparative Gene Finding

  • Ernesto Picardi
  • Graziano Pesole
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 609)

Abstract

High-throughput DNA sequencing is increasing the amount of public complete genomes even though a precise gene catalogue for each organism is not yet available. In this context, computational gene finders play a key role in producing a first and cost-effective annotation. Nowadays a compilation of gene prediction tools has been made available to the scientific community and, despite the high number, they can be divided into two main categories: (1) ab initio and (2) evidence based. In the following, we will provide an overview of main methodologies to predict correct exon–intron structures of eukaryotic genes falling in such categories. We will take into account also new strategies that commonly refine ab initio predictions employing comparative genomics or other evidence such as expression data. Finally, we will briefly introduce metrics to in house evaluation of gene predictions in terms of sensitivity and specificity at nucleotide, exon, and gene levels as well.

Key words

gene prediction gene finder ab initio prediction hidden Markov models similarity searches expression data gene prediction accuracy 

Notes

Acknowledgments

This work was supported by the projects VIGNA (Ministero Politiche Agrigole e Forestali), LIBI – Laboratorio Internazionale di Bioinformatica (Fondo Italiano Ricerca di Base, Ministero dell’ Università e della Ricerca), Laboratorio per la Bioinformatica e la Biodiversità Molecolare (Ministero dell’Università e della Ricerca), Telethon, and AIRC.

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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Ernesto Picardi
    • 1
  • Graziano Pesole
    • 1
  1. 1.Dipartimento di Biochimica e Biologia Molecolare “E. Quagliariello”University of BariBariItaly

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