Identification of ovarian cancer driver genes by using module network integration of multi-omics data.
about
Strategies for Integrated Analysis of Genetic, Epigenetic, and Gene Expression Variation in Cancer: Addressing the ChallengesGlioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features.A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity.CaMoDi: a new method for cancer module discoverySystematic analysis of somatic mutations impacting gene expression in 12 tumour types.Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information.Integration of phytochemicals and phytotherapy into cancer precision medicine.Tumor suppressor candidate 3 (TUSC3) prevents the epithelial-to-mesenchymal transition and inhibits tumor growth by modulating the endoplasmic reticulum stress response in ovarian cancer cells.Multi-omic approaches for characterization of hepatocellular carcinoma.MethylMix: an R package for identifying DNA methylation-driven genesPancancer analysis of DNA methylation-driven genes using MethylMix.Mathematics of the Integrative Cancer Biology Program.Module Analysis Captures Pancancer Genetically and Epigenetically Deregulated Cancer Driver Genes for Smoking and Antiviral Response.Epigenetic regulation of gene expression in cancer: techniques, resources and analysis.Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.A computational framework for complex disease stratification from multiple large-scale datasets.Integrative pathway-based survival prediction utilizing the interaction between gene expression and DNA methylation in breast cancer
P2860
Q26766390-DB077E4E-0155-4F9F-B0FC-5C7B13300A3AQ30820677-AA055833-4AF4-4312-B399-8C65B131BAC9Q33767347-F49278FD-E312-4C99-8E5B-1F11100E05D8Q35538488-1469F14D-D7BE-44F6-AEAB-42027857A743Q36145927-7E4E4306-F7F1-4D06-A7BE-03499C0225F6Q38429590-4E6E1210-1C38-41B7-9A1B-CABC616F8A16Q38780465-7FB3038A-9352-4989-9840-0032FAF66C3CQ38904136-BEBA3E3D-5D78-41FB-8E5F-645BB42F3559Q38923591-7D142604-A595-485F-94B4-D85821FF251CQ41069610-C8D2D054-0C85-46AF-89A5-60C86C05109BQ42237233-AF29099F-C043-451E-B476-F8513F3579B0Q45778405-E386667E-AEAA-4275-A0FA-1CD0C47AF615Q47563785-2C4B779E-1201-4C7A-BE0A-C236A27AD5CAQ47664340-8015380F-8166-4029-9FBD-1D0284F8B096Q52602401-78992BB8-97AC-4F44-AFEA-ABD00018CF27Q55139050-F97B14DB-679F-415A-9261-4292FA1EAD8CQ58739264-5B9AE87F-BB1F-4F44-AE27-EC7B559BEAE6
P2860
Identification of ovarian cancer driver genes by using module network integration of multi-omics data.
description
2013 nî lūn-bûn
@nan
2013 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Identification of ovarian canc ...... tegration of multi-omics data.
@ast
Identification of ovarian canc ...... tegration of multi-omics data.
@en
type
label
Identification of ovarian canc ...... tegration of multi-omics data.
@ast
Identification of ovarian canc ...... tegration of multi-omics data.
@en
prefLabel
Identification of ovarian canc ...... tegration of multi-omics data.
@ast
Identification of ovarian canc ...... tegration of multi-omics data.
@en
P2093
P2860
P356
P1433
P1476
Identification of ovarian canc ...... tegration of multi-omics data.
@en
P2093
Branimir I Sikic
Sylvia K Plevritis
Victor Villalobos
P2860
P304
P356
10.1098/RSFS.2013.0013
P577
2013-08-01T00:00:00Z