{\alpha}-HMM: A Graphical Model for RNA Folding
Biomolecules
2024-01-09 v1 Machine Learning
Abstract
RNA secondary structure is modeled with the novel arbitrary-order hidden Markov model ({\alpha}-HMM). The {\alpha}-HMM extends over the traditional HMM with capability to model stochastic events that may be in influenced by historically distant ones, making it suitable to account for long-range canonical base pairings between nucleotides, which constitute the RNA secondary structure. Unlike previous heavy-weight extensions over HMM, the {\alpha}-HMM has the flexibility to apply restrictions on how one event may influence another in stochastic processes, enabling efficient prediction of RNA secondary structure including pseudoknots.
Keywords
Cite
@article{arxiv.2401.03571,
title = {{\alpha}-HMM: A Graphical Model for RNA Folding},
author = {Sixiang Zhang and Aaron J. Yang and Liming Cai},
journal= {arXiv preprint arXiv:2401.03571},
year = {2024}
}
Comments
14 pages, 5 figures, 1 table