PSAC-6mA: 6mA site identifier using self-attention capsule network based on sequence-positioning.
Introduction
DNA N6-methyladenine (6mA) modifications play a pivotal role in the regulation of growth, development, and
diseases in organisms. As a significant epigenetic marker, 6mA modifications extensively participate in the
intricate regulatory networks of the genome. Hence, gaining a profound understanding of how 6mA is intricately
involved in these biological processes is imperative for deciphering the gene regulatory networks within or ganisms. In this study, we propose PSAC-6mA (Position-self-attention Capsule-6mA), a sequence-location-based
self-attention capsule network. The positional layer in the model enables positional relationship extraction and
independent parameter setting for each base position, avoiding parameter sharing inherent in convolutional
approaches. Simultaneously, the self-attention capsule network enhances dimensionality, capturing correlation
information between capsules and achieving exceptional results in feature extraction across multiple spatial
dimensions within the model. Experimental results demonstrate the superior performance of PSAC-6mA in
recognizing 6mA motifs across various species.