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BMEI
2008
IEEE
15 years 4 months ago
Using Phylogenetic Relationships to Improve the Inference of Transcriptional Regulatory Networks
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...
Xiuwei Zhang, Maryam Zaheri, Bernard M. E. Moret
RECOMB
2003
Springer
15 years 10 months ago
Phylogenetically and spatially conserved word pairs associated with gene expression changes in yeasts
Background: Transcriptional regulation in eukaryotes often involves multiple transcription factors binding to the same transcription control region, and to understand the regulato...
Derek Y. Chiang, Alan M. Moses, Manolis Kamvysseli...
RECOMB
2002
Springer
15 years 10 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
ALIFE
2008
14 years 9 months ago
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...
BMCBI
2008
98views more  BMCBI 2008»
14 years 9 months ago
GBNet: Deciphering regulatory rules in the co-regulated genes using a Gibbs sampler enhanced Bayesian network approach
Background: Combinatorial regulation of transcription factors (TFs) is important in determining the complex gene expression patterns particularly in higher organisms. Deciphering ...
Li Shen, Jie Liu, Wei Wang