Search Results for "bayesian" - Page 5
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Showing 177 open source projects for "bayesian"
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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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bagemass
Bayesian age and mass estimates for transiting planet host stars
Source code, makefile and README for installation of software used for the analysis in Maxted, Serenelli & Southworth, "Bayesian mass and age estimates for transiting exoplanet host stars", A&A 575, 36, 2015. -
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Bayesian Estimated Core Genome
A pipeline for estimating the core genome of a set of genome sequences
...BIGSdb: Scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 2010, 11:595. 2. van Tonder AJ, Mistry S, et al.Defining the estimated core genome of bacterial populations using a Bayesian decision model. (under review) 3. Krzywinski M, Schein J et al. Circos: an information aesthetic for comparative genomics. Genome Res 2009, 19:1639-1645. -
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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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MARAGAP
MARAGAP - Modular Approach to Reference Assisted Genome Assembly Pi...
...MARAGAP uses an algorithmic approach to detect and correct inversions and deletions, a De-Bruijn graph based approach to infer the insertions, an affine-match affine-gap local alignment tool to estimate the locations of those insertions and a Bayesian estimation framework for SNPs. -
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BBNanalysis
Bayesian Belief Network Analysis & Validation
A tool for analysis of Bayesian Belief Networks/Decision Networks in Genie 2.0 (.xdsl) format. Developed as a part of the HELICOPTER project (http://www.helicopter-aal.eu). -
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vbTPM
Variational Bayes for tethered particle motion
...Preprint: http://arxiv.org/abs/1402.0894 If you use this code, please cite our work: Stephanie Johnson, Jan-Willem van de Meent, Rob Phillips, Chris H. Wiggins, and Martin Lindén Multiple LacI-mediated loops revealed by Bayesian statistics and tethered particle motion. Nucleic Acids Research (2014), doi: 10.1093/nar/gku563 -
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We developed a novel mining pipeline, inGAP, which is guided by a Bayesian principle to detect single nucleotide polymorphisms, insertion and deletions by comparing high-throughput pyrosequencing reads with a reference genome of related organisms.
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Bycom
Bycom can do methylcytosine calling (5mC calling) from BS-seq.
...There's no softwares or methods identify methylcytosines considering the cell heterozygosis caused by multicellular sequencing. Bycom introduced it along with the sequencing errors and unconverson rate based on the Bayesian model. 2. Several parameters in Bycom could be set as what the users want to, such as depth threshold, quality control value, conversion rate, processor number. 3. Bycom do the mapping based on BSMAP, and provide the parameters using in the alignment. -
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phcfM
R package for modelling anthropogenic deforestation
...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time. -
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StabLe
An algorithm for learning stable graphical models from data
...Stable random variables are motivated by the central limit theorem for densities with (potentially) unbounded variance and can be thought of as natural generalizations of the Gaussian distribution to skewed and heavy-tailed phenomenon. SG models are multi-variate stable distributions that represent Bayesian networks whose edges encode linear dependencies amongst random variables. A preprint version of the manuscript describing stable graphical models is available at http://arxiv.org/abs/1404.4351. -
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msBayes allows complex and flexible phylogeographic inference. More specifically, you can test the simultaneous divergence (TSD) of multiple population (species) pairs. It uses approximate Bayesian computation (ABC) under a hierarchical model.
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ABM-Calibration-SensitivityAnalysis
Codes and Data for Calibration and Sensitivity Analysis of ABM
...Full Factorial Design 2. Simple Random Sampling 3. Latin Hypercube Sampling 4. Quasi-Newton Method 5. Simulated Annealing 6. Genetic Algorithm 7. Approximate Bayesian Computation b. Sensitivity Analysis: 1. Local SA 2. Morris Screening 3. DoE 4. Partial (Rank) Correlation Coefficient 5. Standardised (Rank) Regression Coefficient 6. Sobol' 7. eFAST 8. FANOVA Decomposition Have also a look on our other projects: http://www.uni-goettingen.de/de/315075.html -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
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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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dbacl - digramic Bayesian classifier
commandline multiclass email and text filter
dbacl is a general purpose digramic Bayesian text classifier. It can learn text documents you provide, and then compare new input with the learned categories. It can be used for spam filtering, or within your own shell scripts. Sometimes it plays che -
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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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High Frequency Based Volatility Modeling
A GNU C and Java High Frequency Volatility Modeling Toolkit
...The model is described in full detail by Shephard and Sheppard in http://www.nuff.ox.ac.uk/users/shephard/papers/heavy.pdf. Access to functions for forecasting volatility, distribution analysis, and Bayesian estimation are also available. Many of the features have been tested and seem to work. Bugs and breakdowns are always inevitable and the package will continuously be updated in the future as improvements are made. -
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JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
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Provide a reference implementation of Moving Taylor Bayesian Regression, a method for nonparametric multi-dimensional function estimation with correlated errors from finite samples, as a Python package based on SciPy
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ABC-DynF
Adaptive Bayesian Classifier with Dynamic Features
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AdPreqFr4SL
Adaptive Prequential Learning Framework
The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we adapt the structure. ... -
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Averaged N-Dependence Estimators - AnDE
AnDE implements A1DE and A2DE
...Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. Machine Learning. 86(2):233-272. -
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...Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. Machine Learning. 86(2):233-272.
