Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer

Journal of Biomedical Informatics

Volumn 56, Issue , 2015, Pages 220-228

  Kim, Dokyoon ^a   Li, Ruowang ^a   Dudek, Scott M ^a   Ritchie, Marylyn D ^a,b  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b GEISINGER HEALTH SYSTEM   (United States)

Author keywords

Breast cancer; Data integration; Interaction between multi omics data; Survival prediction; TCGA

Indexed keywords

ALKYLATION; BIOINFORMATICS; DIAGNOSIS; DISEASES; FORECASTING; GENE EXPRESSION; GENES;

BINARY CLASSIFICATION APPROACH; BREAST CANCER; GRAMMATICAL EVOLUTION; HETEROGENEOUS DISEASE; INTERACTION BETWEEN MULTI-OMICS DATA; MEAN ABSOLUTE DIFFERENCES; SURVIVAL PREDICTION; TCGA;

DATA INTEGRATION;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOINFORMATICS; BREAST CANCER; CANCER SURVIVAL; COMPUTER SIMULATION; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; DATA ANALYSIS; DNA METHYLATION; GENE DOSAGE; GENE EXPRESSION; GENOME ANALYSIS; GENOMICS; HUMAN; INFORMATION PROCESSING; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MULTI DIMENSIONAL OMICS DATA; PREDICTING CENSORED SURVIVAL DATA; PREDICTION; PRIORITY JOURNAL; PROCESS DEVELOPMENT; PROTEIN EXPRESSION; SURVIVAL TIME; ALGORITHM; BIOLOGY; BREAST TUMOR; DISEASE COURSE; EPIGENETICS; FEMALE; GENE EXPRESSION PROFILING; GENETICS; HUMAN GENOME; MEDICAL INFORMATICS; METABOLISM; MORTALITY; PROCEDURES; PROGNOSIS; PROPORTIONAL HAZARDS MODEL; SOFTWARE; STATISTICAL MODEL; SURVIVAL ANALYSIS; TREATMENT OUTCOME;

PROTEOME; TRANSCRIPTOME;

ALGORITHMS; BREAST NEOPLASMS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATA COLLECTION; DISEASE PROGRESSION; DNA METHYLATION; EPIGENOMICS; FEMALE; GENE EXPRESSION PROFILING; GENOME, HUMAN; GENOMICS; HUMANS; MEDICAL INFORMATICS; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); PROGNOSIS; PROPORTIONAL HAZARDS MODELS; PROTEOME; SOFTWARE; SURVIVAL ANALYSIS; TRANSCRIPTOME; TREATMENT OUTCOME;

EID: 84938594824     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2015.05.019     Document Type: Article

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