The fact that a large majority of mammalian genes are subject to alternative splicing indicates that this phenomenon represents a major mechanism for increasing proteome complexity. Here, we provide an overview of current methods for the computational prediction of alternative splicing based on the alignment of genome and transcript sequences. Specific features and limitations of different approaches and software are discussed, particularly those affecting prediction accuracy and assembly of alternative transcripts. © 2006 Oxford University Press.

Bonizzoni, P., Pesole, G., Rizzi, R. (2006). Computational Methods for Alternative Splicing Prediction. BRIEFINGS IN FUNCTIONAL GENOMICS & PROTEOMICS, 5(1), 46-51 [10.1093/bfgp/ell011].

Computational methods for alternative splicing prediction

BONIZZONI, PAOLA;RIZZI, RAFFAELLA
2006

Abstract

The fact that a large majority of mammalian genes are subject to alternative splicing indicates that this phenomenon represents a major mechanism for increasing proteome complexity. Here, we provide an overview of current methods for the computational prediction of alternative splicing based on the alignment of genome and transcript sequences. Specific features and limitations of different approaches and software are discussed, particularly those affecting prediction accuracy and assembly of alternative transcripts. © 2006 Oxford University Press.
Articolo in rivista - Articolo scientifico
Alternative Splicing, Gene Regulation, Algorithm, Software, Comparative Genomics
English
46
51
6
Bonizzoni, P., Pesole, G., Rizzi, R. (2006). Computational Methods for Alternative Splicing Prediction. BRIEFINGS IN FUNCTIONAL GENOMICS & PROTEOMICS, 5(1), 46-51 [10.1093/bfgp/ell011].
Bonizzoni, P; Pesole, G; Rizzi, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/12347
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