BUSCA (http://busca.biocomp. unibo.it), is a novel web server that integrates different computational tools for predicting protein subcellular localization. BUSCA combines methods for identifying signal and transit peptides (DeepSig and TPpred3), GPI-anchors (PredGPI) and transmembrane domains (ENSEMBLE3.0 and BetAware) with tools for discriminating subcellular localization of both globular and membrane proteins (BaCelLo, MemLoci and SChloro). Outcomes from the different tools are processed and integrated for annotating subcellular localization of both eukaryotic and bacterial protein sequences. We benchmark BUSCA against protein targets derived from recent CAFA experiments and other specific data sets, reporting performance at the state-of-the-art. BUSCA scores better than all other evaluated methods on 2732 targets from CAFA2, with a F1 value equal to 0.49 and among the best methods when predicting targets from CAFA3. We propose BUSCA as an integrated and accurate resource for the annotation of protein subcellular localization. BUSCA is available at http://busca.biocomp. unibo.it.

Savojardo, C., Martelli, P.L., Fariselli, P., Profiti, G., Casadio, R. (2018). BUSCA is a web server for predicting subcellular localization of proteins.

BUSCA is a web server for predicting subcellular localization of proteins

Savojardo, Castrense;Martelli, Pier Luigi;Profiti, Giuseppe;Casadio, Rita
2018

Abstract

BUSCA (http://busca.biocomp. unibo.it), is a novel web server that integrates different computational tools for predicting protein subcellular localization. BUSCA combines methods for identifying signal and transit peptides (DeepSig and TPpred3), GPI-anchors (PredGPI) and transmembrane domains (ENSEMBLE3.0 and BetAware) with tools for discriminating subcellular localization of both globular and membrane proteins (BaCelLo, MemLoci and SChloro). Outcomes from the different tools are processed and integrated for annotating subcellular localization of both eukaryotic and bacterial protein sequences. We benchmark BUSCA against protein targets derived from recent CAFA experiments and other specific data sets, reporting performance at the state-of-the-art. BUSCA scores better than all other evaluated methods on 2732 targets from CAFA2, with a F1 value equal to 0.49 and among the best methods when predicting targets from CAFA3. We propose BUSCA as an integrated and accurate resource for the annotation of protein subcellular localization. BUSCA is available at http://busca.biocomp. unibo.it.
2018
Savojardo, C., Martelli, P.L., Fariselli, P., Profiti, G., Casadio, R. (2018). BUSCA is a web server for predicting subcellular localization of proteins.
Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Profiti, Giuseppe; Casadio, Rita
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/656330
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