Molecular subtyping of cancer: current status and moving toward clinical applications
Cancer is a collection of genetic diseases, with large phenotypic differences and genetic
heterogeneity between different types of cancers and even within the same cancer type …
heterogeneity between different types of cancers and even within the same cancer type …
Missing value imputation for gene expression data: computational techniques to recover missing data from available information
Microarray gene expression data generally suffers from missing value problem due to a
variety of experimental reasons. Since the missing data points can adversely affect …
variety of experimental reasons. Since the missing data points can adversely affect …
FABIA: factor analysis for bicluster acquisition
Motivation: Biclustering of transcriptomic data groups genes and samples simultaneously. It
is emerging as a standard tool for extracting knowledge from gene expression …
is emerging as a standard tool for extracting knowledge from gene expression …
Gene expression profiling of 1200 pancreatic ductal adenocarcinoma reveals novel subtypes
L Zhao, H Zhao, H Yan - BMC cancer, 2018 - Springer
Background Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of
cancer related death in the world with a five-year survival rate of less than 5%. Not all PDAC …
cancer related death in the world with a five-year survival rate of less than 5%. Not all PDAC …
FleBiC: Learning classifiers from high-dimensional biomedical data using discriminative biclusters with non-constant patterns
R Henriques, SC Madeira - Pattern Recognition, 2021 - Elsevier
The discovery of discriminative patterns from high-dimensional data offers the possibility to
learn from informative subspaces and pattern-centric features, paving the way to associative …
learn from informative subspaces and pattern-centric features, paving the way to associative …
Quality measures for gene expression biclusters
B Pontes, R Girldez, JS Aguilar-Ruiz - PloS one, 2015 - journals.plos.org
An noticeable number of biclustering approaches have been proposed proposed for the
study of gene expression data, especially for discovering functionally related gene sets …
study of gene expression data, especially for discovering functionally related gene sets …
Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate visualization
Background The DNA microarray technology allows the measurement of expression levels
of thousands of genes under tens/hundreds of different conditions. In microarray data, genes …
of thousands of genes under tens/hundreds of different conditions. In microarray data, genes …
Finding correlated biclusters from gene expression data
Extracting biologically relevant information from DNA microarrays is a very important task for
drug development and test, function annotation, and cancer diagnosis. Various clustering …
drug development and test, function annotation, and cancer diagnosis. Various clustering …
Biclustering of gene expression data by correlation-based scatter search
Background The analysis of data generated by microarray technology is very useful to
understand how the genetic information becomes functional gene products. Biclustering …
understand how the genetic information becomes functional gene products. Biclustering …
Evolutionary optimized fuzzy reasoning with mined diagnostic patterns for classification of breast tumors in ultrasound
Abstract Computer-aided-diagnostic (CAD) techniques are of great help in facilitating the
diagnosis of breast ultrasound (BUS) images. Conventional CAD approaches segment the …
diagnosis of breast ultrasound (BUS) images. Conventional CAD approaches segment the …