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Boltzmann machine learning and regularization methods for inferring evolutionary fields and couplings from a multiple sequence alignment
Both averages smoothly change and converge, but their learning profiles are very different between learning methods.
Selection originating from protein stability/foldability: Relationships between protein folding free energy, sequence ensemble, and fitness
A protein folding theory indicates that homologous sequences obey a canonical ensemble characterized by $\exp(-\Delta G_{ND}/k_B T_s)$ or by $\exp(- G_{N}/k_B T_s)$ if an amino acid composition is kept constant, where $\Delta G_{ND} \equiv G_N - G_D$, $G_N$ and $G_D$ are the native and denatured free energies, and $T_s$ is selective temperature.
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