This document discusses using a boosted categorical restricted Boltzmann machine to predict splice junctions in DNA sequences. It presents categorical gradient as a way to handle the class imbalance problem in splice junction prediction. It shows results on how categorical gradient and boosting improve the prediction of splice junctions, including both canonical and non-canonical splice sites.

1. Boosted Categorical Restricted Boltzmann Machine
for Computational Prediction of Splice Junctions
Taehoon Lee SungrohYoon
Advanced Computing Laboratory
Electrical and Computer Engineering
Seoul National University
Motivation
Categorical Gradient
(Splice) Junction Prediction: Extremely Class-Imbalanced Problem
Results: Effects of Categorical Gradient
Boosted Contrastive Divergence
Results: Effects of Boosting
Results: Improved Junction Prediction Performance Results: Identification of Non-Canonical Splice Sites Conclusion