OpenDinTest is a OpenOffice-Calc-Sheet for statistical Data-Analysis according to the german industry-norm DIN 32645. <br> <br> OpenDinTest ist eine OpenOffice-Calc-Datei zur statistischen Auswertung von Messdaten nach der DIN 32645. <br>
The project would include the development of XUL, CSS and Javascript components to assist biologists in sequence manipulations, data mining, data analysis, etc.).
Databases to aid Metabolomics projects providing storage functionality for raw and preprocessed data, and integration with existing data analysis environments.
CalPyLab is an opensource data acquisition and (light) analysis software suite for scientific laboratories. The goal of this project is to provide a lightweight replacement for lab-view, to provide a quick and easy way to connect to your equipment.
Import width files into MySQL, manipulate and export back to fixed width. Useful for health data analysis or *whatever*. Includes Thompson Reuters Care Discovery 3000 data file definition. Windows, OS X, Linux Requires PHP 5.3.x and MySQL 5.1.x
This project is a fork of the CERN Program Library is a large collection of general purpose libraries/ This program is oriented to needs of a physics laboratory that is general mathematics, data analysis, detectors simulation, data-handling etc...
The project have moved and is alive at http://opencernlib.tuxfamily.org/
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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CNV-WebStore is an integrated platform to analyse, store, visualise and interpret CopyNumber Variation data. Analysis is supported for Illumina data, all CNV-reports and raw data can be imported after third-party analysis. Contact system admin at http://cnv-webstore.uantwerpen.be for installation scripts
The repository has been moved to: https://github.com/wojdyr/fityk. Fityk is nonlinear curve-fitting and data analysis software. It is specialized in fitting peaks (bell-shaped functions like Gaussian, Loretzian, Pearson7, Voigt) to experimental data.
LaCor is intended for physical data analysis in High Energy Physics field.
It was originally designed to aid in lambda hyperon correlations research in the Selex@FNAL experiment, but it should be useful for similar studies.
GODASM is the brief of ".Gff Organized Data Analysis System for Microarray Studies". Private programs, GODA system, had been successful developed in 2008 at CGMH,Taiwan. Now the project will transfer GODAs to open-source based system.
Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
A MATLAB-based software package for microbiological research designed to detect and outline bacterial cells in microscopy images and to analyze fluorescence signal inside them.
VISPA is a novel development environment for high energy physics analyses, based on a combination of graphical and textual steering. The main goal of VISPA is to support users in prototyping, performing, and verifying a data analysis of any complexity.
pyastrolib is a python library providing professional astronomers a robust set of tools for astronomical data analysis. This project will provide all the functionality as NASA's IDL Astronomy User's Library in addition to other planned features.
Logbus-ng consists in a set of tools to aid developers perform Log Analysis in all the stages: log generation, collection, distribution, storage and analysis. It is designed specifically for Field Failure Data Analysis in critical distributed systems
OpenSource Development of (SmartGrid) Data Analysis Platform based on OpenPDC and Cloud Computing Technology. * Source Codes - http://nephee.sourceforge.net, Main Project (Info, Planning, News) , http://nephee.or.kr, http://twitter.com/nepheer
DbViz produces plots of data contained in MySQL databases. Data can be viewed by looking at line graphs, xy scatter plots, and bar graphs. This greatly simplifies data analysis.