Measurement uncertainties with Python.
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported.
Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.
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).
Stand-alone software tool for the interactive CE analysis of microarray data. The software is a user-friendly and allows on-the-fly study of CE
This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.
BigBang/Horizon is a proteomics data analysis pipeline with focus on the shotgun LC/MSMS workflow.
Learning Stochastic Discrete Event Systems
Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes.
This is a Matlab software package for single molecule FRET data analysis.
An R package implementation of a consensus clustering methodology. This package allows users to perform re-sampling statistics based clustering using multiple clustering algorithms to assess the robustness of both clusters and members of clusters.
Temporary test project
test *only* 1) nr3, Poisson distribution 2) mixture model
Set your statistical data free!
Manage statistical data using an editor written in the open source Python programming language and save files in a portable CSV format.
This project is a prototype of a framework for Social Network Analysis created at INRIA. It provides methods for fetching, preparing, clustering and analyzing data from online Social Networks. Currently it has support only for the Twitter network.
The Quality Control Assistant is a utility for quality assurance. Included are shipment analysis functions (confidence interval calculation) and a production control module (error band calculation)
Classic Texas Hold'Em Poker game in python.
MooGraph is an utility to produce interactive dynamical graphs from statistical data. Deliberately inspired to GapMinder, it represents the evolution of multivariate data in time by means of coloured bubbles of variable sizes on an (x,y) plot.
Befasst sich spielerisch mit dem "Infinite-Monkey-Theorem" (http://de.wikipedia.org/wiki/Infinite-Monkey-Theorem). Deals with the "Infinite-Monkey-Theorem" in a playful way (http://en.wikipedia.org/wiki/Infinite_monkey_theorem)
A set of components for doing text mining in Java. The target audience are other text mining developers who can use or extend these components.
An application built onto the Open Table Explorer engine for the acquisition and analysis of home energy consumption and solar energy production.Moved to github as Open Table Explorer
Provide a .NET object model to support computation of minimum, maximum, average of primitive types exported through properties by any object.
This project examines techniques to model three-dimensional rigid body motion using the geometric algebra of Dual Quaternions and how such models compare to more traditional models when used in underconstrained filtering applications.
F@H League Web App is a simple ASP.Net Web application that allows you to create a League of Folding@Home Teams you are interested in and view a range of league tables, statistics and Graphs.
Software to cluster protein sequences into functionally similar groups. Journal reference: http://bioinformatics.oxfordjournals.org/cgi/content/short/24/16/1765