Search Results for "bayesian"
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Showing 18 open source projects for "bayesian"
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...Citation: 1. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007 Aug;73(16):5261-7. 2. Wang Q, Cole JR. Updated RDP taxonomy and RDP Classifier for more accurate taxonomic classification. Microbiol Resour Announc. 2024 Apr 11;13(4):e0106323.
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DEBay
Deconvolutes qPCR data to estimate cell-type-specific gene expression
DEBay: Deconvolution of Ensemble through Bayes-approach DEBay estimates cell type-specific gene expression by deconvolution of quantitative PCR data of a mixed population. It will be useful in experiments where the segregation of different cell types in a sample is arduous, but the proportion of different cell types in the sample can be measured. DEBay uses the population distribution data and the qPCR data to calculate the relative expression of the target gene in different cell types in... -
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faif
C++ header only library with AI and bioinformatics algorithms
C++ header only library, small and fast; Naive Bayesian Classifier, Decision Tree Classifier (ID3), DNA/RNA nucleotide second structure predictor, timeseries management, timeseries prediction, generic Evolutionary Algorithm, generic Hill Climbing algorithm and others. -
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BayesAss
Bayesian Inference of Recent Migration Using Multilocus Genotypes
Inference of recent migration rates between populations using multi-locus marker genotype data. -
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BayesRate
Bayesian estimation of diversification rates
BayesRate is a program to estimate speciation and extinction rates from dated phylogenies in a Bayesian framework. The methods are described in: Silvestro, D., Schnitzler, J. and Zizka, G. (2011) A Bayesian framework to estimate diversification rates and their variation through time and space. BMC Evolutionary Biology, 11, 311 Silvestro D., Zizka G. & Schulte K. (2014) Disentangling the effects of key innovations on the diversification of Bromelioideae (Bromeliaceae). ... -
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StatAlign
An extendable statistical multiple alignment tool.
StatAlign is an extendable software package for Bayesian analysis of Protein, DNA and RNA sequences. Multiple alignments, phylogenetic trees and evolutionary parameters are co-estimated in a Markov Chain Monte Carlo framework, allowing for reliable measurement of the accuracy of the results. This approach eliminates common artifacts that traditional methods suffer from, at the cost of increased computational time. -
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BiomeNet
BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES
...Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. ... -
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FamSeq
Variant calling on the basis of pedigree information
...FamSeq accommodates de novo mutations and can perform variant calling at chromosome X. To accommodate variations in data complexity, FamSeq consists of three distinct implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit. -
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MCTIMME
Microbial Counts Trajectories Infinite Mixture Model Engine
MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab. -
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abc-sde
approximate Bayesian computation for stochastic differential equations
A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. -
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Bayesian Network tools in Java (BNJ) is an open-source suite of software tools for research and development using graphical models of probability. It is published by the Kansas State University Laboratory for Knowledge Discovery in Databases (KDD).
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imDEV
Tools for multivariate data visualization, exploration and analysis.
You may also like some newer work: http://createdatasol.com/ Project imDEV is an application of RExcel, which seamlessly integrates Excel and R for tasks focused on multivariate data visualization, exploration, and analysis. Interactive modules for dimensional reduction (imPCA), prediction (imPLS), feature selection, analysis of correlation (imCorrelations) and generation of networked structures (imGraph) provide an integrated environment for systems level analysis of multivariate data. -
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BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
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This is a reference implementation of snoBAC, a Bayesian Classifier designed to predict box H/ACA snoRNAs in Caenorhabditis nematode genomes. For details of algorithm and data, see Wang and Ruvinsky (2009) RNA in press.
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A C++ library for Bayesian computation, including a collection of more generally-applicable utilities.
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Java/XML toolkit for research using Bayesian networks and other graphical models of probability (exact and approximate inference, structure learning, etc.)
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