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Topology and static response of interaction networks in molecular biology

Topology and static response of interaction networks in molecular biology

http://www.wikidata.org/entity/Q35102759

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The carbon assimilation network in Escherichia coli is densely connected and largely sign-determined by directions of metabolic fluxes Classification of microarray data using gene networks Comparative analysis of the transcription-factor gene regulatory networks of E. coli and S. cerevisiae Inferring the role of transcription factors in regulatory networks Introduction: statistical mechanics of molecular and cellular biological systems Propagation of genetic variation in gene regulatory networks.Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network Relating network rigidity, time scale hierarchies, and expression noise in gene networks.Biologically inspired computing framework for solving two-point boundary value problems using differential evolution

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P2860

Topology and static response of interaction networks in molecular biology

http://www.wikidata.org/entity/Q35102759

description

2006 nî lūn-bûn

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2006 թուականի Փետրուարին հրատարակուած գիտական յօդուած

@hyw

2006 թվականի փետրվարին հրատարակված գիտական հոդված

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2006年の論文

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2006年論文

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2006年論文

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2006年論文

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2006年論文

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2006年論文

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2006年论文

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name

Topology and static response of interaction networks in molecular biology

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Topology and static response of interaction networks in molecular biology

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Topology and static response of interaction networks in molecular biology

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Topology and static response of interaction networks in molecular biology

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Topology and static response of interaction networks in molecular biology

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Topology and static response of interaction networks in molecular biology

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Journal of the Royal Society Interface

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Topology and static response of interaction networks in molecular biology

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P2093

Michel Le Borgne

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Philippe Veber

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P2860

The control of flux

A linear steady-state treatment of enzymatic chains. General properties, control and effector strength

Peroxisome proliferators induce mouse liver stearoyl-CoA desaturase 1 gene expression

Analysis of censored and incomplete survival data using flowgraph models.

Feedback regulation in the lactose operon: a mathematical modeling study and comparison with experimental data.

Protein network inference from multiple genomic data: a supervised approach.

Qualitative analysis of the relation between DNA microarray data and behavioral models of regulation networks.

Qualitative simulation of genetic regulatory networks using piecewise-linear models.

Response experiments for nonlinear systems with application to reaction kinetics and genetics.

Untangling the wires: a strategy to trace functional interactions in signaling and gene networks.

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185-196

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scholarly article

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10.1098/RSIF.2005.0092

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6

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3

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Ovidiu Radulescu

Sandrine Lagarrigue

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2006-02-01T00:00:00Z

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6937069

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16849230

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1618492

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