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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.