Sample scale-free gene regulatory network using gene ontology.
Currently there are various approaches to the reconstruction of gene regulatory networks from different sources of data. However, none of these methods incorporates explicitly scale-free property, one of the most important features of the targeted network, into their algorithms. In this paper, several network sampling strategies are explored on a set assembled from previous published gene interactions in yeast, expecting to reconstruct regulatory networks that are scale-free.
Chen
Guanrao
G
Department of Computer Science, University of Illinois at Chicago, IL 60607, USA. gchen4@uic.edu
Larsen
Peter
P
Almasri
Eyad
E
Dai
Yang
Y
D000465:Algorithms; D019295:Computational Biology / Q000295:instrumentation / Q000379:methods*; D003198:Computer Simulation; D020869:Gene Expression Profiling; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D005800:Genes, Fungal; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D012984:Software