Gene prediction is one of the most challenging tasks in genome analysis, for which many tools have been developed and are still evolving. In this paper, we present a novel gene pr...
Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nanshen...
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
Background: S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challe...
Leander Schietgat, Celine Vens, Jan Struyf, Hendri...
Most decision tree classifiers are designed to keep class histograms for single attributes, and to select a particular attribute for the next split using said histograms. In this ...
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...