Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data

Zhiwen Yu, Hantao Chen, +4 authors Le Li
Published 2015 in
IEEE/ACM Transactions on Computational Biology…

Abstract

Performing clustering analysis is one of the important research topics in cancer discovery using gene expression profiles, which is crucial in facilitating the successful diagnosis and treatment of cancer. While there are quite a number of research works which perform tumor clustering, few of them considers how to incorporate fuzzy theory together with an… (More)

DOI: 10.1109/TCBB.2014.2359433

Clustering by Local Gravitation.

Zhiqiang Wang, Zhiwen Yu, +4 authors Jun Zhang
IEEE transactions on cybernetics
2017

Bi-level and Bi-objective p-Median Type Problems for Integrative Clustering: Application to Analysis of Cancer Gene-Expression and Drug-Response Data

Anton V. Ushakov, Xenia Klimentova, Igor Vasilyev
IEEE/ACM Transactions on Computational Biology…
2016

Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data

Abstract

Topics

13 Figures and Tables

Cited By

Progressive Semisupervised Learning of Multiple Classifiers

A New Kind of Nonparametric Test for Statistical Comparison of Multiple Classifiers Over Multiple Datasets

A cost-sensitive rotation forest algorithm for gene expression data classification

Clustering by Local Gravitation.

Clustering cancer gene expression data by projective clustering ensemble

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

Feature Selection on High Dimensional Data Using Wrapper Based Subset Selection

A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routing

Bi-level and Bi-objective p-Median Type Problems for Integrative Clustering: Application to Analysis of Cancer Gene-Expression and Drug-Response Data

Tensor Manifold Discriminant Projections for Acceleration-Based Human Activity Recognition

References

Serrated carcinomas form a subclass of colorectal cancer with distinct molecular basis

Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma.

Exploratory Consensus of Hierarchical Clusterings for Melanoma and Breast Cancer

Fuzzy ensemble clustering based on random projections for DNA microarray data analysis

Consensus Based Ensembles of Soft Clusterings

Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative.

Identifying distinct classes of bladder carcinoma using microarrays

Microarray analysis reveals distinct gene expression profiles among different histologic types of endometrial cancer.

Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling.

Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses.

Slides referencing similar topics

Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data

Abstract

Topics

13 Figures and Tables

Cited By

Progressive Semisupervised Learning of Multiple Classifiers

A New Kind of Nonparametric Test for Statistical Comparison of Multiple Classifiers Over Multiple Datasets

A cost-sensitive rotation forest algorithm for gene expression data classification

Clustering by Local Gravitation.

Clustering cancer gene expression data by projective clustering ensemble

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

Feature Selection on High Dimensional Data Using Wrapper Based Subset Selection

A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routing

Bi-level and Bi-objective p-Median Type Problems for Integrative Clustering: Application to Analysis of Cancer Gene-Expression and Drug-Response Data

Tensor Manifold Discriminant Projections for Acceleration-Based Human Activity Recognition

References

Serrated carcinomas form a subclass of colorectal cancer with distinct molecular basis

Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma.

Exploratory Consensus of Hierarchical Clusterings for Melanoma and Breast Cancer

Fuzzy ensemble clustering based on random projections for DNA microarray data analysis

Consensus Based Ensembles of Soft Clusterings

Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative.

Identifying distinct classes of bladder carcinoma using microarrays

Microarray analysis reveals distinct gene expression profiles among different histologic types of endometrial cancer.

Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling.

Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses.

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Slides referencing similar topics