Template-based intervention in Boolean network models of biological systems

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Template-based intervention in Boolean network models of biological systems

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2014 nî lūn-bûn

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2014年の論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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Template-based intervention in Boolean network models of biological systems

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Template-based intervention in Boolean network models of biological systems

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Template-based intervention in Boolean network models of biological systems

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Template-based intervention in Boolean network models of biological systems

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Template-based intervention in Boolean network models of biological systems

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Template-based intervention in Boolean network models of biological systems

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P1476

Template-based intervention in Boolean network models of biological systems

@en

P2093

Michael P Verdicchio

http://www.w3.org/2001/XMLSchema#string

Seungchan Kim

http://www.w3.org/2001/XMLSchema#string

P2860

Metabolic stability and epigenesis in randomly constructed genetic nets

The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in Drosophila melanogaster

The yeast cell-cycle network is robustly designed

Advances to Bayesian network inference for generating causal networks from observational biological data.

Platelet-derived growth factor mediates survival of leukemic large granular lymphocytes via an autocrine regulatory pathway.

Dynamical and structural analysis of a T cell survival network identifies novel candidate therapeutic targets for large granular lymphocyte leukemia.

Application of in silico approaches to predicting drug--drug interactions.

Network model of survival signaling in large granular lymphocyte leukemia.

Intervention in a family of Boolean networks.

Intervention in context-sensitive probabilistic Boolean networks.

P2888

s13637-014-0011-4

P304

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P31

scholarly article

P356

10.1186/S13637-014-0011-4

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P478

2014

http://www.w3.org/2001/XMLSchema#string

P577

2014-07-19T00:00:00Z

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P5875

266317317

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P6179

1048465738

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28194161

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P932

5270454

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