2 citations · 3 across the 5 of their papers we have counts for
6 papers
Broadly Applicable Approximate MCMC for Switching Stochastic Differential Equations Using Uniformization and Time-Conditioned Factorized Neural Likelihood Estimation
Shion Hosoda, Michiaki Hamada
Switching stochastic differential equations (SSDEs) describe continuous-time dynamics whose parameters switch according to a latent regime process that follows a continuous-time Ma…
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
Takahiro Mimori, Michiaki Hamada
Phylogenetic inference, grounded in molecular evolution models, is essential for understanding the evolutionary relationships in biological data. Accounting for the uncertainty of…
Beyond similarity assessment: Selecting the optimal model for sequence alignment via the Factorized Asymptotic Bayesian algorithm
Taikai Takeda, Michiaki Hamada
Pair Hidden Markov Models (PHMMs) are probabilistic models used for pairwise sequence alignment, a quintessential problem in bioinformatics. PHMMs include three types of hidden sta…
RNA secondary structure prediction from multi-aligned sequences
Michiaki Hamada
It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. H…
Generalized Centroid Estimators in Bioinformatics
Michiaki Hamada, Hisanori Kiryu, Wataru Iwasaki +1
In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those…
Fighting against uncertainty: An essential issue in bioinformatics
Michiaki Hamada
Many bioinformatics problems, such as sequence alignment, gene prediction, phylogenetic tree estimation and RNA secondary structure prediction, are often affected by the "uncertain…