ABSTRACT

CONTENTS 13.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 13.2 Genetic Regulatory Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 508 13.3 Boolean Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 510 13.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 518 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519

The term functional genomics refers to the study of how genes affect biological mechanisms and phenotype, in particular by applying large-scale and high-throughput experimental methods. The application of computational methods to these and other related problems is referred to as computational genomics. This discipline has been highly influenced by data mining, partly due to the availability of large data sets and databases. Although data mining, as a discipline, is quite broad and lies at the intersection of statistics, machine learning, pattern recognition, and artificial intelligence,1 there are a number of challenging and important problems in computational genomics that can benefit from the application of engineering principles and methodologies, the latter being characterized by systems-level modeling and simulation.