Advances to Bayesian network inference for generating causal networks from observational biological data.
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Comparison of co-expression measures: mutual information, correlation, and model based indicesSize matters: network inference tackles the genome scaleRegulatory network inferred using expression data of small sample size: application and validation in erythroid systemElucidation of pathways driving asthma pathogenesis: development of a systems-level analytic strategyDifferential network analysis in human cancer researchReverse engineering and identification in systems biology: strategies, perspectives and challengesRoot systems biology: integrative modeling across scales, from gene regulatory networks to the rhizosphereComputational inference of neural information flow networksQuantitative and logic modelling of molecular and gene networksCharacterizing dynamic changes in the human blood transcriptional networkIdentifying biological network structure, predicting network behavior, and classifying network state with High Dimensional Model Representation (HDMR)Gene regulatory network modeling via global optimization of high-order dynamic Bayesian networkInferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancerPartially observed bipartite network analysis to identify predictive connections in transcriptional regulatory networksIntegrating external biological knowledge in the construction of regulatory networks from time-series expression data.Model averaging strategies for structure learning in Bayesian networks with limited data.ENNET: inferring large gene regulatory networks from expression data using gradient boostingSatellite remote sensing data can be used to model marine microbial metabolite turnover.Detangling complex relationships in forensic data: principles and use of causal networks and their application to clinical forensic science.Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?S100A4 and its role in metastasis – computational integration of data on biological networks.Multilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.Constructing gene regulatory networks for long term photosynthetic light acclimation in Arabidopsis thaliana.Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge.Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations.A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression data.Reconstruction of genetic association networks from microarray data: a partial least squares approach.Inferring the gene network underlying the branching of tomato inflorescence.A Combined PLS and Negative Binomial Regression Model for Inferring Association Networks from Next-generation Sequencing Count Data.Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks.Inferring cellular networks--a review.Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks.Rank-based edge reconstruction for scale-free genetic regulatory networksPredicting transcriptional regulatory interactions with artificial neural networks applied to E. coli multidrug resistance efflux pumps.High throughput interaction data reveals degree conservation of hub proteins.Coordinated regulation of virulence during systemic infection of Salmonella enterica serovar Typhimurium.Variable selection and dependency networks for genomewide data.Learning robust cell signalling models from high throughput proteomic data.Beyond element-wise interactions: identifying complex interactions in biological processes.Using mechanistic Bayesian networks to identify downstream targets of the sonic hedgehog pathway.
P2860
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P2860
Advances to Bayesian network inference for generating causal networks from observational biological data.
description
2004 nî lūn-bûn
@nan
2004 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2004 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
name
Advances to Bayesian network i ...... observational biological data.
@ast
Advances to Bayesian network i ...... observational biological data.
@en
type
label
Advances to Bayesian network i ...... observational biological data.
@ast
Advances to Bayesian network i ...... observational biological data.
@en
prefLabel
Advances to Bayesian network i ...... observational biological data.
@ast
Advances to Bayesian network i ...... observational biological data.
@en
P2093
P356
P1433
P1476
Advances to Bayesian network i ...... observational biological data.
@en
P2093
Alexander J Hartemink
Paul P Wang
P304
P356
10.1093/BIOINFORMATICS/BTH448
P407
P577
2004-07-29T00:00:00Z