Year: 2024
Type: preprint
Abstract: RNA secondary structure is modeled with the novel arbitrary-order hidden Markov model (α-HMM). The α-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 α-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.
Source: arXiv (Cornell University)
Authors: Zhang, Sixiang, Yang, Aaron J., Cai, Liming
Institution: University of Georgia
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4390722536