Gene Regulatory Network
Mostrando 13-24 de 194 artigos, teses e dissertações.
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13. Reconciling Gene Expression Data With Known Genome-Scale Regulatory Network Structures
The availability of genome-scale gene expression data sets has initiated the development of methods that use this data to infer transcriptional regulatory networks. Alternatively, such regulatory network structures can be reconstructed based on annotated genome information, well-curated databases, and primary research literature. As a first step toward recon
Cold Spring Harbor Laboratory Press.
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14. Estimating Coarse Gene Network Structure from Large-Scale Gene Perturbation Data
Large scale gene perturbation experiments generate information about the number of genes whose activity is directly or indirectly affected by a gene perturbation. From this information, one can numerically estimate coarse structural network features such as the total number of direct regulatory interactions and the number of isolated subnetworks in a transcr
Cold Spring Harbor Laboratory Press.
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15. Xenopus as a model system to study transcriptional regulatory networks
Development is controlled by a complex series of events requiring sequential gene activation. Understanding the logic of gene networks during development is necessary for a complete understanding of how genes contribute to phenotype. Pioneering work initiated in the sea urchin and Drosophila has demonstrated that reasonable transcriptional regulatory network
National Academy of Sciences.
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16. Dissecting the PhoP regulatory network of Escherichia coli and Salmonella enterica
Genetic and genomic approaches have been successfully used to assign genes to distinct regulatory networks. However, the present challenge of distinguishing differentially regulated genes within a network is particularly hard because members of a given network tend to have similar regulatory features. We have addressed this challenge by developing a method,
National Academy of Sciences.
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17. CARRIE web service: automated transcriptional regulatory network inference and interactive analysis
We present an intuitive and interactive web service for CARRIE (Computational Ascertainment of Regulatory Relationships Inferred from Expression). CARRIE is a computational method that analyzes microarray and promoter sequence data to infer a transcriptional regulatory network from the response to a specific stimulus. This service displays an interactive gra
Oxford University Press.
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18. Importance of Input Perturbations and Stochastic Gene Expression in the Reverse Engineering of Genetic Regulatory Networks: Insights From an Identifiability Analysis of an In Silico Network
Gene expression profiles are an increasingly common data source that can yield insights into the functions of cells at a system-wide level. The present work considers the limitations in information content of gene expression data for reverse engineering regulatory networks. An in silico genetic regulatory network was constructed for this purpose. Using the i
Cold Spring Harbor Laboratory Press.
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19. Rapid evolution of expression and regulatory divergences after yeast gene duplication
Although gene duplication is widely believed to be the major source of genetic novelty, how the expression or regulatory network of duplicate genes evolves remains poorly understood. In this article, we propose an additive expression distance between duplicate genes, so that the evolutionary rate of expression divergence after gene duplication can be estimat
National Academy of Sciences.
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20. Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana
A novel approach for modeling gene-regulatory networks, based on graphical Gaussian modeling, is used to create a network for the isoprenoid biosynthesis pathway in Arabidopsis.
BioMed Central.
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21. Computational inference of transcriptional regulatory networks from expression profiling and transcription factor binding site identification
We have developed a computational method for transcriptional regulatory network inference, CARRIE (Computational Ascertainment of Regu latory Relationships Inferred from Expression), which combines microarray and promoter sequence analysis. CARRIE uses sources of data to identify the transcription factors (TFs) that regulate gene expression changes in respon
Oxford University Press.
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22. Evolution of transcription factors and the gene regulatory network in Escherichia coli
The most detailed information presently available for an organism’s transcriptional regulation network is that for the prokaryote Escherichia coli. In order to gain insight into the evolution of the E.coli regulatory network, we analysed information obtainable for the domains and protein families of the transcription factors and regulated genes. About thre
Oxford University Press.
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23. An extended transcriptional regulatory network of Escherichia coli and analysis of its hierarchical structure and network motifs
Recent studies of genome-wide transcriptional regulatory network (TRN) revealed several intriguing structural and dynamic features of gene expression at a system level. Unfortunately, the network under study is often far from complete. A critical question is thus how much the network is incomplete and to what extent this would affect the results of analysis.
Oxford University Press.
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24. Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling
While the fundamental building blocks of biology are being tabulated by the various genome projects, microarray technology is setting the stage for the task of deducing the connectivity of large-scale gene networks. We show how the perturbation of carefully chosen genes in a microarray experiment can be used in conjunction with a reverse engineering algorith
The National Academy of Sciences.