New methods, essentially based on hidden Markov models (HMM) and neural networks (NN), can predict the topography of both β-barrel and all-α membrane proteins with high accuracy and a low rate of false positives and false negatives. These methods have been integrated in a suite of programs to filter proteomes of Gram-negative bacteria, searching for new membrane proteins. Copyright © 2003 John Wiley & Sons, Ltd.
The prediction of membrane protein structure and genome structural annotation / Martelli P.L.; Fariselli P.; Tasco G.; Casadio R.. - In: COMPARATIVE AND FUNCTIONAL GENOMICS. - ISSN 1531-6912. - STAMPA. - 4:4(2003), pp. 406-409. [10.1002/cfg.308]
The prediction of membrane protein structure and genome structural annotation
Martelli P. L.;Fariselli P.;Tasco G.;Casadio R.
2003
Abstract
New methods, essentially based on hidden Markov models (HMM) and neural networks (NN), can predict the topography of both β-barrel and all-α membrane proteins with high accuracy and a low rate of false positives and false negatives. These methods have been integrated in a suite of programs to filter proteomes of Gram-negative bacteria, searching for new membrane proteins. Copyright © 2003 John Wiley & Sons, Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
