3 papers
q-bio.BM2026
Boltzmann Machine Learning with a Parallel, Persistent Markov chain Monte Carlo method for Estimating Evolutionary Fields and Couplings from a Protein Multiple Sequence Alignment
Sanzo Miyazawa
The inverse Potts problem for estimating evolutionary single-site fields and pairwise couplings in homologous protein sequences from their single-site and pairwise amino acid frequ…
q-bio.PE2024
Selection originating from protein stability/foldability: Relationships between protein folding free energy, sequence ensemble, and fitness
Sanzo Miyazawa
Assuming that mutation and fixation processes are reversible Markov processes, we prove that the equilibrium ensemble of sequences obeys a Boltzmann distribution with $\exp(4N_e m(…
q-bio.PE2024
Boltzmann machine learning and regularization methods for inferring evolutionary fields and couplings from a multiple sequence alignment
Sanzo Miyazawa
The inverse Potts problem to infer a Boltzmann distribution for homologous protein sequences from their single-site and pairwise amino acid frequencies recently attracts a great de…