Splam: an accurate deep learning-based splice site predictor

   2022-10 - Present

   Baltimore, MD

   Center of Computational Biology, Johns Hopkins University

   Transcriptome

     BioRxiv

     Mihaele Pertea      Steven Salzberg  

  Introduction

I am developing SpliceNN, a residual-convolutional-neural-network-based deep learning model, aiming to filter out misaligned spliced reads.