Modelling gene functional linkages using yeast microarray data.
Understanding how genes are functionally related requires efficient algorithms to model networks from expression data. We report a heuristic search algorithm called Two-Level Simulated Annealing (TLSA) that is more likely to find the global optimal network structure compared to conventional simulated annealing and other searching schemes. We have applied this method to search for a global optimised network structure from a synthetic data set and an expression data set of S. cerevisiae mutants. We have achieved better precision and recall compared to other searching algorithms and are able to map relationships more accurately among functionally-linked genes.
Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona 85287, USA. tie.wang@asu.edu
Tie
T
Wang
Guoliang
G
Xue
Jeffrey W
JW
Touchman
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D012441:Saccharomyces cerevisiae / Q000235:genetics*