Cargando…

Investigating perturbed pathway modules from gene expression data via structural equation models

BACKGROUND: It is currently accepted that the perturbation of complex intracellular networks, rather than the dysregulation of a single gene, is the basis for phenotypical diversity. High-throughput gene expression data allow to investigate changes in gene expression profiles among different conditi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Pepe, Daniele, Grassi, Mario
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2014
Materias:	Methodology Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052286/ https://www.ncbi.nlm.nih.gov/pubmed/24885496 http://dx.doi.org/10.1186/1471-2105-15-132

Ejemplares similares

Extracting expression modules from perturbational gene expression compendia
por: Maere, Steven, et al.
Publicado: (2008)

Applying dynamic Bayesian networks to perturbed gene expression data
por: Dojer, Norbert, et al.
Publicado: (2006)

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data
por: Lee, Hyeonjeong, et al.
Publicado: (2017)

Dynamic probabilistic threshold networks to infer signaling pathways from time-course perturbation data
por: Kiani, Narsis A, et al.
Publicado: (2014)

Detect the early-warning signals of diseases based on signaling pathway perturbations on a single sample
por: Huo, Yanhao, et al.
Publicado: (2022)

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method
por: Wang, Ting, et al.
Publicado: (2014)

Development of an Elliptical Perturbation System that provides unexpected perturbations during elliptical walking (the EPES system)
por: Sade, Shoval, et al.
Publicado: (2023)

Multiple network algorithm for epigenetic modules via the integration of genome-wide DNA methylation and gene expression data
por: Ma, Xiaoke, et al.
Publicado: (2017)

Estimation of health effects of prenatal methylmercury exposure using structural equation models
por: Budtz-Jørgensen, Esben, et al.
Publicado: (2002)

Structural Equation Modeling of In silico Perturbations
por: Li, Jianying, et al.
Publicado: (2021)

Basic Equations and Computing Procedures for Frailty Modeling of Carcinogenesis: Application to Pancreatic Cancer Data
por: Mdzinarishvili, Tengiz, et al.
Publicado: (2013)

Using random walks to identify cancer-associated modules in expression data
por: Petrochilos, Deanna, et al.
Publicado: (2013)

BRCA-Pathway: a structural integration and visualization system of TCGA breast cancer data on KEGG pathways
por: Kim, Inyoung, et al.
Publicado: (2018)

Using large-scale perturbations in gene network reconstruction
por: MacCarthy, Thomas, et al.
Publicado: (2005)

Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes
por: Dhoble, Abhishek S., et al.
Publicado: (2018)

SEMgsa: topology-based pathway enrichment analysis with structural equation models
por: Grassi, Mario, et al.
Publicado: (2022)

Motif-guided sparse decomposition of gene expression data for regulatory module identification
por: Gong, Ting, et al.
Publicado: (2011)

On Differential Gene Expression Using RNA-Seq Data
por: Lee, Juhee, et al.
Publicado: (2011)

Case-Based Retrieval Framework for Gene Expression Data
por: Anaissi, Ali, et al.
Publicado: (2015)

Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems
por: Shu, Le, et al.
Publicado: (2016)

ModuleFinder and CoReg: alternative tools for linking gene expression modules with promoter sequences motifs to uncover gene regulation mechanisms in plants
por: Holt, Kathryn E, et al.
Publicado: (2006)

Gene perturbation and intervention in context-sensitive stochastic Boolean networks
por: Zhu, Peican, et al.
Publicado: (2014)

Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation
por: Hira, Zena M., et al.
Publicado: (2016)

Automation of gene assignments to metabolic pathways using high-throughput expression data
por: Popescu, Liviu, et al.
Publicado: (2005)

Semi-supervised consensus clustering for gene expression data analysis
por: Wang, Yunli, et al.
Publicado: (2014)

Utilizing trait networks and structural equation models as tools to interpret multi-trait genome-wide association studies
por: Momen, Mehdi, et al.
Publicado: (2019)

Adaptive initial step size selection for Simultaneous Perturbation Stochastic Approximation
por: Ito, Keiichi, et al.
Publicado: (2016)

Bayesian differential analysis of gene regulatory networks exploiting genetic perturbations
por: Li, Yan, et al.
Publicado: (2020)

Independent component analysis of Alzheimer's DNA microarray gene expression data
por: Kong, Wei, et al.
Publicado: (2009)

Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression data
por: Li, Min, et al.
Publicado: (2012)

A search engine to identify pathway genes from expression data on multiple organisms
por: Chen, Chunnuan, et al.
Publicado: (2007)

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence
por: Jiang, Hao, et al.
Publicado: (2017)

Assessment of network perturbation amplitudes by applying high-throughput data to causal biological networks
por: Martin, Florian, et al.
Publicado: (2012)

Using hospitalization for ambulatory care sensitive conditions to measure access to primary health care: an application of spatial structural equation modeling
por: Hossain, Md Monir, et al.
Publicado: (2009)

Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone
por: de Anda-Jáuregui, Guillermo, et al.
Publicado: (2019)

A novel biclustering approach with iterative optimization to analyze gene expression data
por: Sutheeworapong, Sawannee, et al.
Publicado: (2012)

Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways
por: Pey, Jon, et al.
Publicado: (2013)

A novel wearable device to deliver unconstrained, unpredictable slip perturbations during gait
por: Rasmussen, Corbin M., et al.
Publicado: (2019)

TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery
por: Liu, Yusong, et al.
Publicado: (2021)

An investigation of gene-gene interactions in dose-response studies with Bayesian nonparametrics
por: Beam, Andrew L, et al.
Publicado: (2015)

Cannot write session to /tmp/vufind_sessions/sess_vrg28bb68d2o1r42hbariert3d