Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
This paper introduces a method for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring clusters. The proposed ...
Background: With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experiment...
Jesse M. Engreitz, Alexander A. Morgan, Joel Dudle...
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...
Large repositories of source code create new challenges and opportunities for statistical machine learning. Here we first develop Sourcerer, an infrastructure for the automated c...
Erik Linstead, Paul Rigor, Sushil Krishna Bajracha...