Scalable Reverse Engineering of Nonlinear Gene Networks
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Motivation: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed ...
Background: Proteins are the primary regulatory agents of transcription even though mRNA expression data alone, from systems like DNA microarrays, are widely used. In addition, the regulation process in genetic systems is inherently non-linear in nature, a ...
Motivation: MicroRNAs are small endogenous RNAs that can play important regulatory roles via the RNA-interference pathway by targeting mRNAs for cleavage or translational repression. We propose a computational method to predict miRNA regulatory modules or ...
Motivation: MicroRNAs (miRNAs) are small endogenous RNAs that can play important regulatory roles via the RNA-interference pathway by targeting mRNAs for cleavage or translational repression. We propose a computational method to predict mi ...
Vascular endothelial growth factor-C (VEGF-C) is considered one of the most important factors influencing lymphatic endothelial cell biology. The goal of this work was to characterize the gene expression response by lymphatic endothelial cells (LECs) to VE ...
With the increasing availability of experimental data on gene-gene and protein-protein interactions, modeling of gene regulatory networks has gained a special attention lately. To have a better understanding of these networks it is necessary to capture the ...
Protein-DNA interactions (PDIs) between transcription factors (TFs) and their target genes form the backbone of transcription regulatory networks. Such PDIs can be identified with either a TF or a gene as a starting point. The Gateway-compatible yeast one- ...
The effective reverse engineering of biochemical networks is one of the great challenges of systems biology. The contribution of this paper is two-fold: 1) We introduce a new method for reverse engineering genetic regulatory networks from gene expression d ...
MicroRNAs are a family of small, non-coding RNAs that regulate gene expression in a sequence-specific manner. We propose a computational method to predict miRNA regulatory modules or groups of miRNAs and target genes that are believed to participate cooper ...
In contrast to most primary metabolism genes, the genes involved in secondary metabolism and certain nutrient utilization pathways are clustered in fungi. Recently a nuclear protein, LaeA, was found to be required for the transcription of several secondary ...