380 citations · 1.6k across the 84 of their papers we have counts for
6 papers · 1 filter
DNA-Level Splice Junction Prediction using Deep Recurrent Neural Networks
Byunghan Lee, Taehoon Lee, Byunggook Na +1
A eukaryotic gene consists of multiple exons (protein coding regions) and introns (non-coding regions), and a splice junction refers to the boundary between a pair of exon and intr…
Manifold Regularized Deep Neural Networks using Adversarial Examples
Taehoon Lee, Minsuk Choi, Sungroh Yoon
Learning meaningful representations using deep neural networks involves designing efficient training schemes and well-structured networks. Currently, the method of stochastic gradi…
NASCUP: Nucleic Acid Sequence Classification by Universal Probability
Sunyoung Kwon, Gyuwan Kim, Byunghan Lee +3
Motivated by the need for fast and accurate classification of unlabeled nucleotide sequences on a large scale, we developed NASCUP, a new classification method that captures statis…
DUDE-Seq: Fast, Flexible, and Robust Denoising for Targeted Amplicon Sequencing
Byunghan Lee, Taesup Moon, Sungroh Yoon +1
We consider the correction of errors from nucleotide sequences produced by next-generation targeted amplicon sequencing. The next-generation sequencing (NGS) platforms can provide…
Regularization and Kernelization of the Maximin Correlation Approach
Taehoon Lee, Taesup Moon, Seung Jean Kim +1
Robust classification becomes challenging when each class consists of multiple subclasses. Examples include multi-font optical character recognition and automated protein function…
Will solid-state drives accelerate your bioinformatics? In-depth profiling, performance analysis, and beyond
Sungmin Lee, Hyeyoung Min, Sungroh Yoon
A wide variety of large-scale data has been produced in bioinformatics. In response, the need for efficient handling of biomedical big data has been partly met by parallel computin…