Cluster analysis for gene expression data: a survey

D Jiang, C Tang, A Zhang - IEEE Transactions on knowledge …, 2004 - ieeexplore.ieee.org
DNA microarray technology has now made it possible to simultaneously monitor the
expression levels of thousands of genes during important biological processes and across …

Semi-supervised methods to predict patient survival from gene expression data

E Bair, R Tibshirani - PLoS biology, 2004 - journals.plos.org
An important goal of DNA microarray research is to develop tools to diagnose cancer more
accurately based on the genetic profile of a tumor. There are several existing techniques in …

Discovering local structure in gene expression data: the order-preserving submatrix problem

A Ben-Dor, B Chor, R Karp, Z Yakhini - Proceedings of the sixth annual …, 2002 - dl.acm.org
This paper concerns the discovery of patterns in gene expression matrices, in which each
element gives the expression level of a given gene in a given experiment. Most existing …

[BUCH][B] Design and analysis of DNA microarray investigations

RM Simon, EL Korn, LM McShane, MD Radmacher… - 2003 - Springer
DNA microarrays are an important technology for studying gene expression. With a single
hybridization, the level of expression of thousands of genes, or even an entire genome, can …

Enhanced biclustering on expression data

J Yang, H Wang, W Wang, P Yu - Third IEEE Symposium on …, 2003 - ieeexplore.ieee.org
Microarrays are one of the latest breakthroughs in experimental molecular biology, which
provide a powerful tool by which the expression patterns of thousands of genes can be …

[PDF][PDF] Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach.

L Wolf, A Shashua, D Geman - Journal of Machine Learning Research, 2005 - jmlr.org
The problem of selecting a subset of relevant features in a potentially overwhelming quantity
of data is classic and found in many branches of science. Examples in computer vision, text …

[PDF][PDF] Biclustering microarray data by Gibbs sampling

Q Sheng, Y Moreau, B De Moor - Bioinformatics, 2003 - researchgate.net
Motivation: Gibbs sampling has become a method of choice for the discovery of noisy
patterns, known as motifs, in DNA and protein sequences. Because handling noise in …

Methods for assessing reproducibility of clustering patterns observed in analyses of microarray data

LM McShane, MD Radmacher, B Freidlin, R Yu… - …, 2002 - academic.oup.com
Motivation: Recent technological advances such as cDNA microarray technology have
made it possible to simultaneously interrogate thousands of genes in a biological specimen …

Novel unsupervised feature filtering of biological data

R Varshavsky, A Gottlieb, M Linial, D Horn - Bioinformatics, 2006 - academic.oup.com
Motivation: Many methods have been developed for selecting small informative feature
subsets in large noisy data. However, unsupervised methods are scarce. Examples are …

Novel rank-based statistical methods reveal microRNAs with differential expression in multiple cancer types

R Navon, H Wang, I Steinfeld, A Tsalenko, A Ben-Dor… - PloS one, 2009 - journals.plos.org
Background microRNAs (miRNAs) regulate target genes at the post-transcriptional level and
play important roles in cancer pathogenesis and development. Variation amongst …