Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.

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A Glimpse to Background and Characteristics of Major Molecular Biological Networks Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

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Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.

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2014 nî lūn-bûn

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Untangling statistical and bio ...... r a genomics network ontology.

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Untangling statistical and bio ...... r a genomics network ontology.

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Matthias Dehmer

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ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context

A quantitative description of membrane current and its application to conduction and excitation in nerve

Cardiac Action and Pacemaker Potentials based on the Hodgkin-Huxley Equations

Integrative analysis of cell cycle control in budding yeast

On the epistemological crisis in genomics

Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana

SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms.

Gene regulatory network inference: data integration in dynamic models-a review

Bagging statistical network inference from large-scale gene expression data

ENNET: inferring large gene regulatory networks from expression data using gradient boosting

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10.3389/FGENE.2014.00299

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Benjamin Haibe-Kains

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Amar

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Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.

about

P2860

P2860

Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.

description

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P1476

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