Cargando…

The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

With advances in next-generation sequencing(NGS) technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics d...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lu, Xinguo, Li, Xing, Liu, Ping, Qian, Xin, Miao, Qiumai, Peng, Shaoliang
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2018
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6099653/ https://www.ncbi.nlm.nih.gov/pubmed/29364829 http://dx.doi.org/10.3390/molecules23020183

Ejemplares similares

A novel method to identify gene interaction patterns
por: Lu, Xinguo, et al.
Publicado: (2021)

Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data
por: Lu, Xinguo, et al.
Publicado: (2017)

Identification of ovarian cancer subtype-specific network modules and candidate drivers through an integrative genomics approach
por: Zhang, Di, et al.
Publicado: (2015)

A gene signature based method for identifying subtypes and subtype-specific drivers in cancer with an application to medulloblastoma
por: Chen, Peikai, et al.
Publicado: (2013)

Identifying Cancer Specific Driver Modules Using a Network-Based Method
por: Li, Feng, et al.
Publicado: (2018)

An integrated genomics approach identifies drivers of proliferation in luminal subtype human breast cancer
por: Gatza, Michael L., et al.
Publicado: (2014)

Integrative multi-omic analysis identifies new drivers and pathways in molecularly distinct subtypes of ALS
por: Morello, Giovanna, et al.
Publicado: (2019)

An Effective Graph Clustering Method to Identify Cancer Driver Modules
por: Zhang, Wei, et al.
Publicado: (2020)

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis
por: Cava, Claudia, et al.
Publicado: (2018)

Identifying Hepatocellular Carcinoma Driver Genes by Integrative Pathway Crosstalk and Protein Interaction Network
por: Chen, Wenbiao, et al.
Publicado: (2019)

Identifying modules of cooperating cancer drivers
por: Klein, Michael I, et al.
Publicado: (2021)

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network
por: Wei, Pi-Jing, et al.
Publicado: (2016)

DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies
por: Han, Yi, et al.
Publicado: (2019)

Identifying driver modules based on multi‐omics biological networks in prostate cancer
por: Chen, Zhongli, et al.
Publicado: (2022)

A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph
por: Song, Junrong, et al.
Publicado: (2019)

Identifying breast cancer subtypes associated modules and biomarkers by integrated bioinformatics analysis
por: Wang, Yanwei, et al.
Publicado: (2021)

Identification of Common Driver Gene Modules and Associations between Cancers through Integrated Network Analysis
por: Gao, Bo, et al.
Publicado: (2021)

DriverGenePathway: Identifying driver genes and driver pathways in cancer based on MutSigCV and statistical methods
por: Xu, Xiaolu, et al.
Publicado: (2023)

Identifying potential cancer driver genes by genomic data integration
por: Chen, Yong, et al.
Publicado: (2013)

Integrative network analysis identifies an immune-based prognostic signature as the determinant for the mesenchymal subtype in epithelial ovarian cancer
por: Sheng, Mingyan, et al.
Publicado: (2020)

Corrigendum to article “DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies’’
por: Han, Yi, et al.
Publicado: (2021)

MaxMIF: A New Method for Identifying Cancer Driver Genes through Effective Data Integration
por: Hou, Yingnan, et al.
Publicado: (2018)

DIPG-35. IDENTIFYING DRIVER-SPECIFIC VULNERABILITIES IN PAEDIATRIC HIGH GRADE GLIOMA SUBTYPES
por: De Cola, Antonella, et al.
Publicado: (2023)

Integrated analysis of recurrent properties of cancer genes to identify novel drivers
por: D'Antonio, Matteo, et al.
Publicado: (2013)

An Integrative Analysis to Identify Driver Genes in Esophageal Squamous Cell Carcinoma
por: Sawada, Genta, et al.
Publicado: (2015)

The Integrated Analyses of Driver Genes Identify Key Biomarkers in Thyroid Cancer
por: Xu, Qili, et al.
Publicado: (2020)

AI-Driver: an ensemble method for identifying driver mutations in personal cancer genomes
por: Wang, Haoxuan, et al.
Publicado: (2020)

A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping
por: Sathyanarayanan, Anita, et al.
Publicado: (2019)

Identifying driver genes involving gene dysregulated expression, tissue-specific expression and gene-gene network
por: Song, Junrong, et al.
Publicado: (2019)

NMFNA: A Non-negative Matrix Factorization Network Analysis Method for Identifying Modules and Characteristic Genes of Pancreatic Cancer
por: Ding, Qian, et al.
Publicado: (2021)

Identifying overlapping mutated driver pathways by constructing gene networks in cancer
por: Wu, Hao, et al.
Publicado: (2015)

Integrative analysis identifies lincRNAs up- and downstream of neuroblastoma driver genes
por: Rombaut, Dries, et al.
Publicado: (2019)

Integrating multi-type aberrations from DNA and RNA through dynamic mapping gene space for subtype-specific breast cancer driver discovery
por: Xi, Jianing, et al.
Publicado: (2023)

Integrated Analysis of Energy Metabolism Signature-Identified Distinct Subtypes of Bladder Urothelial Carcinoma
por: Zhang, Fan, et al.
Publicado: (2022)

Identification of osteosarcoma driver genes using a network method
por: Si, Zebing, et al.
Publicado: (2020)

A novel network control model for identifying personalized driver genes in cancer
por: Guo, Wei-Feng, et al.
Publicado: (2019)

The Analysis of Relevant Gene Networks Based on Driver Genes in Breast Cancer
por: Qu, Luxuan, et al.
Publicado: (2022)

Integrated genomic analysis identifies clinically relevant subtypes of renal clear cell carcinoma
por: Wu, Peng, et al.
Publicado: (2018)

An Integrated Approach for Identifying Molecular Subtypes in Human Colon Cancer Using Gene Expression Data
por: Wang, Wen-Hui, et al.
Publicado: (2018)

Identifying Breast Cancer Subtype Related miRNAs from Two Constructed miRNAs Interaction Networks in Silico Method
por: Hua, Lin, et al.
Publicado: (2013)

Cannot write session to /tmp/vufind_sessions/sess_c5fr6j6hbe9kep368jrh75a3v9