Search Results for "framework"
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Showing 15 open source projects for "framework"
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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ShinyCardinal
Mass spectrometry imaging data analysis software tool
...ShinyCardinal is built as a desktop application with a conveniently designed graphic user interface to provide users a stable, consistent, and user-friendly data analysis framework. Tutorial videos: https://www.youtube.com/@MSI_WIS/videos -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. ... -
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R portable configures R to work with the PortableApps framework, so that R can be ran from a thumb drive or portable hard drive without leaving artifacts on the computer.
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Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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PMM-Lab
Predictive Microbial Modeling plug-in for KNIME
...Altogether these components are designed to ease and standardize the statistical analysis of experimental microbial data and the development of predictive microbial models (PMM). Users can apply PMM-Lab to proprietary or public data and create bacterial growth / survival / inactivation models. The framework can easily be extended to other model types, e.g. growth/no-growth boundary models. PMM-Lab has been initiated and provided by the Federal Institute for Risk Assessment - BfR (Berlin, Germany). The software is in Beta status. Before using the software you have to read and accept the license and disclaimer (https://sourceforge.net/p/pmmlab/wiki/Disclaimer/). ... -
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BiomeNet
BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES
Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. 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. ... -
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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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abc-sde
approximate Bayesian computation for stochastic differential equations
...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. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/ -
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A software framework to build maps for Neurospora crassa genome based on probabilistic models of meiotic recombination. A netbeans platform application is built to incorporate the computations. Project issues are mainatined at https://freecode4susant.atlassian.net/browse/GENOMEMAP
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Smart Business Texting that Generates PipelineTextUs is the leading text messaging service provider for businesses that want to engage in real-time conversations with customers, leads, employees and candidates. Text messaging is one of the most engaging ways to communicate with customers, candidates, employees and leads. 1:1, two-way messaging encourages response and engagement. Text messages help teams get 10x the response rate over phone and email. Business text messaging has become a more viable form of communication than traditional mediums. The TextUs user experience is intentionally designed to resemble the familiar SMS inbox, allowing users to easily manage contacts, conversations, and campaigns. Work right from your desktop with the TextUs web app or use the Chrome extension alongside your ATS or CRM. Leverage the mobile app for on-the-go sending and responding.
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Binomial Distribution Calculator
A simple to use Binomial Distribution Calculator.
...You can display the calculated data in a table or even graphically. Simultaneously, this application computes the expected value and the standard deviation. To use this app you need to have .NET Framework 4 installed. Contact me: lambdapew-dev@yahoo.de -
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DyMMM
Dynamic Multispecies Metabolic Modeling framework
The Dynamic Multispecies Metabolic Modeling (DyMMM [dĭm]) framework is a mathematical modeling tool that integrates multiple constraint-based metabolic models into a single dynamic community metabolic model. The DyMMM framework was formerly known as the DMMM framework. Please use the following citation for bibliographical purposes: Zhuang, K., Izallalen, M., Mouser, P., Richter, H., Risso, C., Mahadevan, R., & Lovley, D. -
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StatsCollect is a little framework gathering statistics from external sources (social networks, web sites...), stored in pluggable backends. It can be very easily extended thanks to its plugins (currently include Facebook, Myspace, Youtube, Google).
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PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
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Math.NET aims to provide a self contained clean framework for symbolic mathematical (Computer Algebra System) and numerical/scientific computations, including a parser and support for linear algebra, complex differential analysis, system solving and more
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ExoPlanet
GUI based toolkit for running common Machine Learning algorithms.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. ...
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