Variable knot-based spline approximation recursive Bayesian algorithm for the identification of Wiener systems with process noise

2017 ◽  
Vol 90 (4) ◽  
pp. 2293-2303 ◽  
Author(s):  
Shaoxue Jing ◽  
Tianhong Pan ◽  
Zhengming Li
Keyword(s):  
Spline Approximation ◽  
Process Noise ◽  
Bayesian Algorithm ◽  
Wiener Systems ◽  
Recursive Bayesian

scholarly journals Use of Recursive Bayesian Algorithm to Optimise Coronary Artery Disease Diagnostic Pathways

2011 ◽  
Vol 20 ◽  
pp. S45
Author(s):  
J. Rivers ◽  
J. Lefevre ◽  
M. Waterhouse ◽  
I. Smith ◽  
K. Mengersen
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Bayesian Algorithm ◽  
Artery Disease ◽  
Diagnostic Pathways ◽  
Recursive Bayesian

scholarly journals STRONG: metagenomics strain resolution on assembly graphs

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Christopher Quince ◽  
Sergey Nurk ◽  
Sebastien Raguideau ◽  
Robert James ◽  
Orkun S. Soyer ◽  
...  
Keyword(s):  
Time Series ◽  
De Novo ◽  
Single Copy ◽  
Bayesian Algorithm ◽  
Anaerobic Digestor ◽  
Core Genes

AbstractWe introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and stores the coassembly graph prior to variant simplification. This enables the subgraphs and their unitig per-sample coverages, for individual single-copy core genes (SCGs) in each MAG, to be extracted. A Bayesian algorithm, BayesPaths, determines the number of strains present, their haplotypes or sequences on the SCGs, and abundances. STRONG is validated using synthetic communities and for a real anaerobic digestor time series generates haplotypes that match those observed from long Nanopore reads.

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