Inferring transcriptional regulatory networks from geneexpression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong networ...
As more and more genomes are sequenced, evolutionary biologists are becoming increasingly interested in evolution at the level of whole genomes, in scenarios in which the genome e...
Krister M. Swenson, Mark Marron, Joel V. Earnest-D...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Abstract. Can we model the temporal evolution of topics in Web image collections? If so, can we exploit the understanding of dynamics to solve novel visual problems or improve reco...
Modeling Internet growth is important both for understanding the current network and to predict and improve its future. To date, Internet models have typically attempted to explai...