Automated Function Prediction (AFP) of proteins in Multi-species Networks raises challenging computational problems due to the size of the generated network and the lack of scalability of traditional approaches. We present a network-based approach that allows to predict protein functions in a multi-species setting by exploiting homology relationships between species. The method adopts secondary memory-based technologies to efficiently process huge protein networks using ordinary stand-alone machines.

On the automated function prediction of big multi-species networks / M. Re, M. Mesiti, G. Valentini. ((Intervento presentato al convegno Network Biology SIG - ISMB tenutosi a Boston nel 2014.

On the automated function prediction of big multi-species networks

M. Re
Primo
;
M. Mesiti
Secondo
;
G. Valentini
Ultimo
2014

Abstract

Automated Function Prediction (AFP) of proteins in Multi-species Networks raises challenging computational problems due to the size of the generated network and the lack of scalability of traditional approaches. We present a network-based approach that allows to predict protein functions in a multi-species setting by exploiting homology relationships between species. The method adopts secondary memory-based technologies to efficiently process huge protein networks using ordinary stand-alone machines.
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
On the automated function prediction of big multi-species networks / M. Re, M. Mesiti, G. Valentini. ((Intervento presentato al convegno Network Biology SIG - ISMB tenutosi a Boston nel 2014.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/253851
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