Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...
Background: With the completion of the genome sequences of human, mouse, and other species and the advent of high throughput functional genomic research technologies such as biomi...
Peisen Zhang, Jinghui Zhang, Huitao Sheng, James J...
Background: Microarray technology has unveiled transcriptomic differences among tumors of various phenotypes, and, especially, brought great progress in molecular understanding of...
Atsushi Niida, Andrew D. Smith, Seiya Imoto, Shuic...
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
Background: A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be rela...