Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process.
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Network Inference and Biological DynamicsBagging statistical network inference from large-scale gene expression dataAnalysis of effects of meteorological factors on dengue incidence in Sri Lanka using time series data.Short time-series microarray analysis: methods and challenges.Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression DataMultilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data.Judgment algorithm for periodicity of time series data based on Bayesian information criterion.Recursive regularization for inferring gene networks from time-course gene expression profiles.Gene network reconstruction from microarray data.Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiaeTimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach.Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.Reconstruction of Complex Directional Networks with Group Lasso Nonlinear Conditional Granger Causality.Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patientsDiscovering graphical Granger causality using the truncating lasso penalty.Network inference using steady-state data and Goldbeter-Koshland kinetics. [corrected]Signaling network prediction by the Ontology Fingerprint enhanced Bayesian network.A systems biology starter kit for arenaviruses.Inferring regulatory networks by combining perturbation screens and steady state gene expression profiles.Inferring slowly-changing dynamic gene-regulatory networks.A network perspective on nitrogen metabolism from model to crop plants using integrated 'omics' approaches.Genome-wide transcriptomic variations of human lymphoblastoid cell lines: insights from pairwise gene-expression correlations.Structural influence of gene networks on their inference: analysis of C3NET.Correcting for link loss in causal network inference caused by regulator interference.Graph spectral analysis of protein interaction network evolution.Grouped graphical Granger modeling for gene expression regulatory networks discovery.Comment on causality and pathway search in microarray time series experiment.Inference of large-scale gene regulatory networks using regression-based network approach.Probabilistic modeling and machine learning in structural and systems biologySystems-epigenomics inference of transcription factor activity implicates aryl-hydrocarbon-receptor inactivation as a key event in lung cancer development.Bayesian Networks Analysis of Malocclusion Data.Inferring Boolean network structure via correlation.Gene expression network reconstruction by LEP method using microarray data.Heritable stress response dynamics revealed by single-cell genealogy.
P2860
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P2860
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process.
description
2007 nî lūn-bûn
@nan
2007 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2007 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
name
Learning causal networks from ...... vector autoregressive process.
@ast
Learning causal networks from ...... vector autoregressive process.
@en
type
label
Learning causal networks from ...... vector autoregressive process.
@ast
Learning causal networks from ...... vector autoregressive process.
@en
prefLabel
Learning causal networks from ...... vector autoregressive process.
@ast
Learning causal networks from ...... vector autoregressive process.
@en
P2860
P1433
P1476
Learning causal networks from ...... vector autoregressive process.
@en
P2093
Rainer Opgen-Rhein
P2860
P2888
P356
10.1186/1471-2105-8-S2-S3
P478
P577
2007-05-03T00:00:00Z
P6179
1040099297