Semi-supervised recursively partitioned mixture models for identifying cancer subtypes

No abstract is available for this paper.

• Publication year

  2010

• Venue

  Bioinform.

• Publication date

  2010-10-01

• Fields of study

  Medicine, Computer Science, Mathematics

• Identifiers
  DOI 10.1093/bioinformatics/btq470PMID 20834038PMCID PMC2951086
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Gene-specific and global methylation patterns predict outcome in patients with acute myeloid leukemia

  2010cited by this paper
• Gene Expression-Based Classification of Non-Small Cell Lung Carcinomas and Survival Prediction

  2010influential reference
• Comprehensive profiling of DNA methylation in colorectal cancer reveals subgroups with distinct clinicopathological and molecular features

  2010cited by this paper
• Epigenetic profiles distinguish pleural mesothelioma from normal pleura and predict lung asbestos burden and clinical outcome.

  2009cited by this paper
• Differentiation of lung adenocarcinoma, pleural mesothelioma, and nonmalignant pulmonary tissues using DNA methylation profiles.

  2009cited by this paper
• Epigenetic profiling reveals etiologically distinct patterns of DNA methylation in head and neck squamous cell carcinoma.

  2009cited by this paper
• Aging and Environmental Exposures Alter Tissue-Specific DNA Methylation Dependent upon CpG Island Context

  2009cited by this paper
• Association of MicroRNA Expression in Hepatocellular Carcinomas with Hepatitis Infection, Cirrhosis, and Patient Survival

  2008cited by this paper
• Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R

  2008cited by this paper
• A transcriptional fingerprint of estrogen in human breast cancer predicts patient survival.

  2008cited by this paper
• Feature‐Specific Penalized Latent Class Analysis for Genomic Data

  2006cited by this paper
• Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma

  2005cited by this paper
• Bayesian Variable Selection in Clustering High-Dimensional Data

  2005cited by this paper
• Semi-Supervised Methods to Predict Patient Survival from Gene Expression Data

  2004influential reference
• Expression of the secreted frizzled-related protein gene family is downregulated in human mesothelioma

  2004cited by this paper
• Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia.

  2004cited by this paper
• Gene expression profiling identifies clinically relevant subtypes of prostate cancer.

  2004cited by this paper
• Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays

  2003cited by this paper
• Repeated observation of breast tumor subtypes in independent gene expression data sets

  2003cited by this paper
• BMC Bioinformatics BioMed Central Methodology article Tumor classification and marker gene prediction by feature

  2003cited by this paper
• Derivative Estimation and Testing in Generalized Additive Models

  2003cited by this paper
• Model-Based Clustering, Discriminant Analysis, and Density Estimation

  2002cited by this paper
• Gene expression profiling predicts clinical outcome of breast cancer

  2002cited by this paper
• Gene-expression profiles predict survival of patients with lung adenocarcinoma

  2002cited by this paper
• A gene-expression signature as a predictor of survival in breast cancer.

  2002cited by this paper
• Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling

  2000cited by this paper
• Cluster analysis and display of genome-wide expression patterns.

  1998cited by this paper
• Optimal Rate of Convergence for Finite Mixture Models

  1995cited by this paper
• Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis

  1991cited by this paper
• Finding Groups in Data: An Introduction to Cluster Analysis

  1990cited by this paper
• The explained variation in proportional hazards regression

  1990cited by this paper
• Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper

  1977cited by this paper

• Evaluation of agreement between common clustering strategies for DNA methylation-based subtyping of breast tumours.

  2024cites this paper
• A Supervised Clustering Approach for Customer Segmentation in Commercial Banks based on Customer Value

  2024cites this paper
• Outcome-guided spike-and-slab Lasso Biclustering: A Novel Approach for Enhancing Biclustering Techniques for Gene Expression Analysis

  2024cites this paper
• Overlapping coefficient in network-based semi-supervised clustering

  2024influential citation
• MC‐KV: A Prognosis‐Oriented Classifier Based on Semi‐Supervised Learning for Molecular Subtyping of Colorectal Cancer

  2023cites this paper
• An overview of clustering methods with guidelines for application in mental health research.

  2023cites this paper
• The prognostic and biological importance of chromatin regulation-related genes for lung cancer is examined using bioinformatics and experimentally confirmed.

  2023cites this paper
• Genome-Scale Methylation Analysis Identifies Immune Profiles and Age Acceleration Associations with Bladder Cancer Outcomes

  2023cites this paper
• Comparative Transcriptome Profiling Reveals the Genes Involved in Storage Root Expansion in Sweetpotato (Ipomoea batatas (L.) Lam.)

  2022cites this paper
• A Weakly Supervised Clustering Method for Cancer Subgroup Identification

  2022cites this paper
• Fucoxanthin Inactivates the PI3K/Akt Signaling Pathway to Mediate Malignant Biological Behaviors of Non-Small Cell Lung Cancer

  2022cites this paper
• Multi-objective Semi-supervised Clustering for Finding Predictive Clusters

  2022cites this paper
• Network‐based semisupervised clustering

  2021cites this paper
• Multiobjective semisupervised learning with a right‐censored endpoint adapted to the multiple imputation framework

  2021cites this paper
• Investigating the Role of the Human Element in Maritime Accidents using Semi-Supervised Hierarchical Methods

  2021cites this paper
• An Approach to Supervised Learning: Dynamic Multi-Hyperplane Partitioning

  2020cites this paper
• Supervised convex clustering

  2020cites this paper
• Outcome-Guided Disease Subtyping for High-Dimensional Omics Data

  2020cites this paper
• Analyzing high dimensional correlated data using feature ranking and classifiers

  2019cites this paper
• Using a Latent Class Forest to Identify At-Risk Students in Higher Education

  2019influential citation
• Identification of Interaction Clusters Using a Semi-supervised Hierarchical Clustering Method

  2019cites this paper
• Network-based methods for outcome prediction in the "sample space"

  2017cites this paper
• Towards clinically more relevant dissection of patient heterogeneity via survival‐based Bayesian clustering

  2017cites this paper
• AN INTEGRATED SEMI-SUPERVISED CLUSTERING MODEL FOR TIME COURSE GENE EXPRESSION DATA

  2017cites this paper
• Description of exposure profiles for seven environmental chemicals in a US population using recursive partition mixture modeling (RPMM)

  2017cites this paper
• Mining heterogeneous causal effects for personalized cancer treatment

  2017cites this paper
• International Journal of Scientific Research in Computer Science, Engineering and Information Technology

  2016cites this paper
• A weakly supervised clustering method for cancer subgroup identification

  2016cites this paper
• Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization

  2016cites this paper
• CpG island methylation profile in non-invasive oral rinse samples is predictive of oral and pharyngeal carcinoma

  2015cites this paper
• Evolutionary non-linear modelling for selecting vaccines against antigenically variable viruses

  2015cites this paper
• Epigenetics of urothelial carcinoma.

  2015cites this paper
• Placental epigenetic patterning of glucocorticoid response genes is associated with infant neurodevelopment.

  2015cites this paper
• Computational and Statistical Epigenomics

  2015cites this paper
• Mixture Models for Multidimensional Positive Data Clustering with Applications to Image Categorization and Retrieval

  2015cites this paper
• Model-Based Clustering of DNA Methylation Array Data

  2015cites this paper
• Integrative clustering methods for high-dimensional molecular data.

  2014cites this paper
• A recursively partitioned mixture model for clustering time-course gene expression data.

  2014cites this paper
• Fuzzy Preference Based Feature Selection and Semisupervised SVM for Cancer Classification

  2014cites this paper
• Iterative Subsampling in Solution Path Clustering of Noisy Big Data

  2014cites this paper
• Object clustering and recognition using multi-finite mixtures for semantic classes and hierarchy modeling

  2014cites this paper
• Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis

  2014cites this paper
• Tumor hypomethylation at 6p21.3 associates with longer time to recurrence of high-grade serous epithelial ovarian cancer.

  2014cites this paper
• Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning

  2014cites this paper
• Solution Path Clustering with Minimax Concave Penalty and Its Applications to Noisy Big Data

  2014cites this paper
• SURVEY OF GENE-EXPRESSION-BASED CANCER SUBTYPES PREDICTION

  2014cites this paper
• A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression

  2014cites this paper
• Epidemiology of childhood germ cell tumors (GCT): epigenome-wide methylation, differential MiRNA expression, and catchment quality of the CCRN

  2013influential citation
• Review of processing and analysis methods for DNA methylation array data

  2013influential citation
• Gene-Expression-Based Cancer Subtypes Prediction Through Feature Selection and Transductive SVM

  2013cites this paper
• Identification of significant features in DNA microarray data

  2013cites this paper
• A variational Bayes beta Mixture Model for Feature Selection in DNA methylation Studies

  2013cites this paper
• Semi‐supervised clustering methods

  2013cites this paper
• Semi-supervised classification using sparse representation for cancer recurrence prediction

  2013cites this paper
• Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel.

  2013cites this paper
• Identification of biologically relevant subtypes via preweighted sparse clustering

  2013influential citation
• Recursively partitioned mixture model clustering of DNA methylation data using biologically informed correlation structures

  2013cites this paper
• Blood-derived DNA methylation markers of cancer risk.

  2013cites this paper
• Semisupervised Methods for Analyzing High‐dimensional Genomic Data

  2013cites this paper
• Identification of relevant subtypes via preweighted sparse clustering

  2013influential citation
• Peripheral Blood Immune Cell Methylation Profiles Are Associated with Nonhematopoietic Cancers

  2012cites this paper
• Biostatistical Methods in Epigenetic Epidemiology

  2012cites this paper
• A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

  2012cites this paper
• A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform

  2012cites this paper
• Peripheral blood DNA methylation profiles are indicative of head and neck squamous cell carcinoma: An epigenome-wide association study

  2012cites this paper
• Cancer classification through feature selection and transductive SVM using gene microarray data

  2012cites this paper
• SC³: Triple Spectral Clustering-Based Consensus Clustering Framework for Class Discovery from Cancer Gene Expression Profiles

  2012cites this paper
• Reducing confounding and suppression effects in TCGA data: an integrated analysis of chemotherapy response in ovarian cancer

  2012cites this paper
• DNA methylation arrays as surrogate measures of cell mixture distribution

  2012cites this paper
• EPIGENETIC EFFECTS OF IN-UTERO ARSENIC EXPOSURE

  2011cites this paper
• Infant growth restriction is associated with distinct patterns of DNA methylation in human placentas

  2011cites this paper
• Semi-supervised learning improves gene expression-based prediction of cancer recurrence

  2011cites this paper
• DNA methylation array analysis identifies profiles of blood-derived DNA methylation associated with bladder cancer.

  2011cites this paper
• Statistical approaches for the analysis of DNA methylation microarray data

  2011cites this paper
• SHARE @ Children's Mercy SHARE @ Children's Mercy

  year unknowncites this paper