Memory Matching Networks for Genomic Sequence Classification

Understand

When analyzing the genome, researchers have discovered that proteins bind to DNA based on certain patterns of the DNA sequence known as "motifs".

• However, it is difficult to manually construct motifs due to their complexity.
• Recently, externally learned memory models have proven to be effective methods for reasoning over inputs and supporting sets.
• In this work, we present memory matching networks (MMN) for classifying DNA sequences as protein binding sites.