We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outl...
Seiya Imoto, Tomoyuki Higuchi, SunYong Kim, Euna J...
Background: The sequencing of many genomes and tiling arrays consisting of millions of DNA segments spanning entire genomes have made high-resolution copy number analysis possible...
Dmitriy Skvortsov, Diana Abdueva, Michael E. Stitz...
Background: The amount of gene expression data in the public repositories, such as NCBI Gene Expression Omnibus (GEO) has grown exponentially, and provides a gold mine for bioinfo...
Rong Chen, Rohan Mallelwar, Ajit Thosar, Shivkumar...
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
We describe our contribution to the ICMLA2008 "Automated Micro-Array Classification Challenge". The design of our classifier is motivated by the special scenario encounte...
Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel...