Pages that link to "Q33503982"
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The following pages link to Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis (Q33503982):
Displaying 50 items.
- Tensor GSVD of patient- and platform-matched tumor and normal DNA copy-number profiles uncovers chromosome arm-wide patterns of tumor-exclusive platform-consistent alterations encoding for cell transformation and predicting ovarian cancer survival (Q21090556) (← links)
- Strategies for Integrated Analysis of Genetic, Epigenetic, and Gene Expression Variation in Cancer: Addressing the Challenges (Q26766390) (← links)
- Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential (Q26782613) (← links)
- The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders (Q27005952) (← links)
- Development and mining of a volatile organic compound database (Q28234865) (← links)
- Comprehensive molecular characterization of gastric adenocarcinoma (Q28244985) (← links)
- Comprehensive genomic characterization of squamous cell lung cancers (Q28274701) (← links)
- Integrated genomic characterization of endometrial carcinoma (Q28289962) (← links)
- Statistical Methods in Integrative Genomics (Q28385219) (← links)
- The Use of Chemical-Chemical Interaction and Chemical Structure to Identify New Candidate Chemicals Related to Lung Cancer (Q28395836) (← links)
- Breakthroughs in genomics data integration for predicting clinical outcome (Q28708853) (← links)
- Clustering of High Throughput Gene Expression Data (Q28714213) (← links)
- The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups (Q29614700) (← links)
- Signalling pathway database usability: lessons learned (Q30486334) (← links)
- Multilevel omic data integration in cancer cell lines: advanced annotation and emergent properties (Q30590335) (← links)
- JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES. (Q30642591) (← links)
- Bayesian methods for expression-based integration of various types of genomics data. (Q30668548) (← links)
- Exploring TCGA Pan-Cancer data at the UCSC Cancer Genomics Browser (Q30671000) (← links)
- Similarity network fusion for aggregating data types on a genomic scale (Q30742291) (← links)
- SPARSE INTEGRATIVE CLUSTERING OF MULTIPLE OMICS DATA SETS. (Q30768936) (← links)
- Integrative analysis of longitudinal metabolomics data from a personal multi-omics profile (Q30832988) (← links)
- A meta-analysis of multiple matched copy number and transcriptomics data sets for inferring gene regulatory relationships (Q30844284) (← links)
- Integrative clustering methods for high-dimensional molecular data (Q30854282) (← links)
- Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery (Q30971287) (← links)
- Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration (Q30983525) (← links)
- Integrating heterogeneous genomic data to accurately identify disease subtypes (Q31026902) (← links)
- Characterizing Cancer-Specific Networks by Integrating TCGA Data (Q31029870) (← links)
- Integrative methods for analyzing big data in precision medicine (Q31032576) (← links)
- Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer (Q31034941) (← links)
- PINCAGE: probabilistic integration of cancer genomics data for perturbed gene identification and sample classification (Q31035683) (← links)
- Methods for the integration of multi-omics data: mathematical aspects (Q31040819) (← links)
- Integrative clustering of high-dimensional data with joint and individual clusters (Q31049305) (← links)
- Multiplex methods provide effective integration of multi-omic data in genome-scale models (Q31056287) (← links)
- Integrative subtype discovery in glioblastoma using iCluster (Q31059566) (← links)
- A graph theoretical approach to data fusion (Q31060656) (← links)
- Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data (Q31066480) (← links)
- ICM: a web server for integrated clustering of multi-dimensional biomedical data (Q31088370) (← links)
- Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery (Q31108643) (← links)
- Integrative clustering of multi-level omics data for disease subtype discovery using sequential double regularization (Q31122935) (← links)
- Flexible model-based clustering of mixed binary and continuous data: application to genetic regulation and cancer (Q31150084) (← links)
- A review on machine learning principles for multi-view biological data integration (Q31151051) (← links)
- Prediction of years of life after diagnosis of breast cancer using omics and omic-by-treatment interactions. (Q33707489) (← links)
- Clinical Genomics: Challenges and Opportunities (Q33797074) (← links)
- More Is Better: Recent Progress in Multi-Omics Data Integration Methods (Q33804425) (← links)
- Statistical approaches for the analysis of DNA methylation microarray data (Q33881906) (← links)
- Computational prognostic indicators for breast cancer. (Q33921791) (← links)
- Patient-specific data fusion defines prognostic cancer subtypes (Q34058053) (← links)
- Time to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles (Q34071483) (← links)
- Breast cancer patient stratification using a molecular regularized consensus clustering method (Q34119214) (← links)
- Genome-driven integrated classification of breast cancer validated in over 7,500 samples (Q34199428) (← links)