Estimating large-scale signaling networks through nested effect models with intervention effects from microarray data.
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Linear effects models of signaling pathways from combinatorial perturbation data.Refining Pathways: A Model Comparison ApproachR-based software for the integration of pathway data into bioinformatic algorithms.Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression DataLarge scale statistical inference of signaling pathways from RNAi and microarray data.A factor graph nested effects model to identify networks from genetic perturbations.Nested effects models for learning signaling networks from perturbation data.Deterministic Effects Propagation Networks for reconstructing protein signaling networks from multiple interventionsHow to understand the cell by breaking it: network analysis of gene perturbation screensDynamic deterministic effects propagation networks: learning signalling pathways from longitudinal protein array data.Inferring signalling networks from longitudinal data using sampling based approaches in the R-package 'ddepn'Integration of gene expression data with prior knowledge for network analysis and validation.MC EMiNEM maps the interaction landscape of the MediatorA genomic strategy for the functional validation of colorectal cancer genes identifies potential therapeutic targets.Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.A Bayesian network view on nested effects models.Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET.Inferring modulators of genetic interactions with epistatic nested effects models.Cross-talk between AMPK and EGFR dependent Signaling in Non-Small Cell Lung Cancer.Modeling the temporal interplay of molecular signaling and gene expression by using dynamic nested effects models.Analyzing gene perturbation screens with nested effects models in R and bioconductor.Considering unknown unknowns: reconstruction of nonconfoundable causal relations in biological networks.DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity.Improved pathway reconstruction from RNA interference screens by exploiting off-target effects.Single cell network analysis with a mixture of Nested Effects Models
P2860
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P2860
Estimating large-scale signaling networks through nested effect models with intervention effects from microarray data.
description
2008 nî lūn-bûn
@nan
2008 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Estimating large-scale signali ...... effects from microarray data.
@ast
Estimating large-scale signali ...... effects from microarray data.
@en
type
label
Estimating large-scale signali ...... effects from microarray data.
@ast
Estimating large-scale signali ...... effects from microarray data.
@en
prefLabel
Estimating large-scale signali ...... effects from microarray data.
@ast
Estimating large-scale signali ...... effects from microarray data.
@en
P2860
P50
P356
P1433
P1476
Estimating large-scale signali ...... effects from microarray data.
@en
P2093
Mark Fellmann
Tim Beissbarth
P2860
P304
P356
10.1093/BIOINFORMATICS/BTM634
P407
P577
2008-01-28T00:00:00Z