2015/01/19 by Joseph L. Herman, Herman, Joseph L., Adrienn Szabó +5
Biochemistry, Genetics and Molecular Biology · Computer Science · #Algorithms and Data Compression #Bayesian Methods and Mixture Models #Computational Engineering #FOS: Biological sciences #FOS: Computer and information sciences #Finance #Gene expression and cancer classification #Genomics and Phylogenetic Studies #Quantitative Methods (q-bio.QM) #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.1501.04986
openalex publication_date 2015/01/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We outline a procedure for jointly sampling substitution matrices and\nmultiple sequence alignments, according to an approximate posterior\ndistribution, using an MCMC-based algorithm. This procedure provides an\nefficient and simple method by which to generate alternative alignments\naccording to their expected accuracy, and allows appropriate parameters for\nsubstitution matrices to be selected in an automated fashion. In the cases\nconsidered here, the sampled alignments with the highest likelihood have an\naccuracy consistently higher than alignments generated using the standard\nBLOSUM62 matrix.\n