Qualitative reasoning on systematic gene perturbation experiments

Authors:
Francesco Sambo;Barbara Di Camillo
Affiliations:
Department of Information Engineering, University of Padova, Italy;Department of Information Engineering, University of Padova, Italy
Venue:
CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
Year:
2010

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Abstract

Observations of systematic gene perturbation experiments have been proven the most informative for the identification of regulatory relations between genes. For this purpose, we present a novel Qualitative Reasoning approach, based on a qualitative abstraction of DNA-microarray data and on a set of IF-THEN inference rules. Our algorithm exhibits an extremely low rate of false positives, competitive with the state-of-the-art, on both noise-free and noisy simulated data. This, together with the polynomial running time, makes our algorithm an useful tool for systematic gene perturbation experiments, able to identify a subset of the oriented regulatory relations with high reliability and to provide valuable insights on the amount of information conveyed by a set of experiments.