Prediction of phenotype and gene expression for combinations of mutations. - Wikidata - awgldk - TriplyDB

Prediction of phenotype and gene expression for combinations of mutations.

Prediction of phenotype and gene expression for combinations of mutations.

http://www.wikidata.org/entity/Q42860872

about

Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems Epistasis and quantitative traits: using model organisms to study gene-gene interactions Quantitative epistasis analysis and pathway inference from genetic interaction data Maximal extraction of biological information from genetic interaction data Functional maps of protein complexes from quantitative genetic interaction data.Combination chemical genetics A factor graph nested effects model to identify networks from genetic perturbations.A developmental systems perspective on epistasis: computational exploration of mutational interactions in model developmental regulatory networks.Integrating physical and genetic maps: from genomes to interaction networks.Systems cell biology of the mitotic spindle.Markov logic networks in the analysis of genetic data.Predicting protein phenotypes based on protein-protein interaction network.Multiple genetic interaction experiments provide complementary information useful for gene function prediction.Use of pleiotropy to model genetic interactions in a population.Chapter 5: Network biology approach to complex diseases.Dominant PRPF31 mutations are hypostatic to a recessive CNOT3 polymorphism in retinitis pigmentosa: a novel phenomenon of "linked trans-acting epistasis".Discovering pair-wise genetic interactions: an information theory-based approach Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks Weak Epistasis Generally Stabilizes Phenotypes in a Mouse Intercross.Feature Identification of Compensatory Gene Pairs without Sequence Homology in Yeast.Systematic measurement of transcription factor-DNA interactions by targeted mass spectrometry identifies candidate gene regulatory proteins.Inferring gene function and network organization in Drosophila signaling by combined analysis of pleiotropy and epistasis.Prediction of gene phenotypes based on GO and KEGG pathway enrichment scores.Adding more content to screening: reactivation of FOXO as a therapeutic strategy.Towards genome-scale signalling network reconstructions.A systems-biology approach to modular genetic complexity.Past Roadblocks and New Opportunities in Transcription Factor Network Mapping.Dissection of complex gene expression using the combined analysis of pleiotropy and epistasis Predicting the effects of copy-number variation in double and triple mutant combinations.Heritable remodeling of yeast multicellularity by an environmentally responsive prion

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P2860

Prediction of phenotype and gene expression for combinations of mutations.

http://www.wikidata.org/entity/Q42860872

description

2007 nî lūn-bûn

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2007年の論文

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2007年論文

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2007年論文

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2007年論文

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2007年論文

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2007年論文

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2007年论文

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2007年论文

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2007年论文

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name

Prediction of phenotype and gene expression for combinations of mutations.

@en

Prediction of phenotype and gene expression for combinations of mutations.

@nl

type

label

Prediction of phenotype and gene expression for combinations of mutations.

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Prediction of phenotype and gene expression for combinations of mutations.

@nl

prefLabel

Prediction of phenotype and gene expression for combinations of mutations.

@en

Prediction of phenotype and gene expression for combinations of mutations.

@nl

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Molecular Systems Biology

P1476

Prediction of phenotype and gene expression for combinations of mutations.

@en

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Bruz Marzolf

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

Christine Neou

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

Gregory W Carter

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J Patrick Shelby

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

Susanne Prinz

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

Timothy Galitski

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

Vesteinn Thorsson

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P2860

Derivation of genetic interaction networks from quantitative phenotype data

MULTIFACTORIAL GENETICSUNDERSTANDING QUANTITATIVE GENETIC VARIATION

Gene ontology: tool for the unification of biology

A human protein-protein interaction network: a resource for annotating the proteome

Automated modelling of signal transduction networks.

Motifs, themes and thematic maps of an integrated Saccharomyces cerevisiae interaction network

Inferring yeast cell cycle regulators and interactions using transcription factor activities.

Complex genetic interactions in a quantitative trait locus.

Transcriptional regulatory networks in Saccharomyces cerevisiae

Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans

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96

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10.1038/MSB4100137

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3

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2007-03-27T00:00:00Z

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