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BIOINFORMATICS Vol. 00 no. 00 2007

Vol. 00 no. 00 2007
Pages 17
Comparing association network algorithms for reverse
engineering of large scale gene regulatory networks:
synthetic vs real data
Nicola Soranzo a
, Ginestra Bianconi b
, Claudio Altafinia
aSISSA-ISAS, International School for Advanced Studies, via Beirut 2-4, 34014 Trieste, Italy,
bAbdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34014 Trieste, Italy
Motivation: Inferring a gene regulatory network exclusively from
microarray expression profiles is a difficult but important task. The
aim of this work is to compare the predictive power of some of the
most popular algorithms in different conditions (like data taken at equi-
librium or time courses) and on both synthetic and real microarray
data. We are in particular interested in comparing similarity measu-
res both of linear type (like correlations and partial correlations) and
of nonlinear type (mutual information and conditional mutual informa-


Source: Altafini, Claudio - Functional Analysis Sector, Scuola Internazionale Superiore di Studi Avanzati (SISSA)


Collections: Engineering; Mathematics