Open Source Data Analytics Tools

EChem++ is a software system based on an object oriented approach to electrochemical experimentation, simulation, and data analysis. Currently, development emphasis lies on the modelling and simulation as well as the analysis modules.

This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...

mzMatch is a Java collection of small commandline tools specific for metabolomics MS data analysis. The tools are built on top of the PeakML core library, providing mass spectrometry specific functionality and access to the PeakML file format.

Electron diffraction code for the simulation and data analysis of keV electron-molecule scattering.

Set of tools for basic analysis of electrophysiological data. The Python classes show how to call OpenElectrophy functions and save data. The R library applies circular statistics to spike phase data and saves the best von Mises fit and the Rayleigh statistics on the disk. The wavelet coherence analysis is done in R by the package "sowas". Check the module R_coherence to see how we solved that problem. This packages may be useful for people who start using OpenElectrophy and circular statistics in R. If you find errors, please report them. The project is still in development, so in the future you'll get updates.

A framework for image analysis and data analysis, aimed towards microscopy and the needs of current research.

EyeMap is a visualization and analysis tool for text reading eye movement data. It can process Unicode, proportion/non-proportion and spaced/unspaced reading materials, which supports various languages and experiment methods.

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.

GEDAS is a software to perform microarray data analysis with friendly user interface and convenient data display. Currently some commonly used data clustering algorithms have been implemented in this software.

GmanDA is a GPL software for performing qualitative data analysis on mailing-lists and mboxes. It was developed to ease the work with large scale mailing-list archives taken from Gmane.org

HCS Analyzer is an open source software dedicated to High Content Screening data processing and analysis.

HadStat is service on the cloud, allow you to analysis the data on the cloud and return the result in nice graph,this service is free, you can redistribute it and/or modify it under the terms of the GNU General Public License. this service using many technologies , like Hadoop mapreduce, HTML, PHP, Web Service applications, linux server, java, eclipse IDE, with many indicators:Simple moving average (SMA),Exponential moving average (EMA),Smoothed simple moving average (SMMA),Linear weighted moving average (LWMA )on DATA from NYSE daily prices.....

HyPhy is a comprehensive environment for maximum likelihood statistical analysis of genetic sequence data. It includes a large collection of out of the box analyses, a feature-rich graphical user interface for custom data analysis and a scripting languag

The hsdar package contains classes and functions to manage, analyse and simulate hyperspectral data. These might be either spectrometer measurements or hyperspectral images through the interface of rgdal.

Matlab freeware for data analysis, by J. M. Lilly

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.

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.

Larch is a scientific data processing language that is designed to be easy to use for novices and complete enough for advanced data processing and analysis. Larch provides a wide range of functionality for dealing with arrays of scientific data, and basic tools to make it easy to use and organize complex data. Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources. Larch is written in Python and relies heavily on the standard tools for scientific computing with Python (numpy, scipy, matplotlib, and h5py).

A tool for visualisation and analysis of STM and STS results. Currently supports RHK, WinSPM, Nanonis and Createc file formats. Other formats can be added. Tools are made available by plugins and are currently focused on spectroscopy manipulation.

Framework for text mining, data integration and data analysis. Keywords: ontology and graph alignment, relation mining, warehouse, semantic database integration, bioinformatics, systems biology, microarray, Java.

OCL stands for Open Cezeri Library (yet another linear algebra and matrix library). This library provides rapid coding as matlab ease of use. To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. Studies on accesing Leapmotion and Kinect is still under-development. 2- Machine learning: It uses Weka Software tool and some personel coded ML algorithms 3- CMatrix: Special matrix library called as CMatrix meaning Cezeri Maztrix Class. Actually it is regarded as the core of the OCL. CMatrix supports fluent interface and method chaining.

PMM-Lab is an open-source extension to the Konstanz Information Miner (KNIME). It consists of three components: • a library of KNIME nodes (called PMM-Lab), • a library of “standard” workflows • an HSQL database.to store experimental data and microbial models. 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/). If you do not agree, do not use this software.

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

PlateEditor is a free web application to work with multi-well plates, from creation of layouts to data visualization and aggregation. It is primarily designed as a tool to help scientists working in the field of biology to simplify and fasten the process of data analysis. It is fully client-side: files are never transferred to the server, ensuring complete security and privacy of research data. It doesn't require any installation. - PlateEditor is available at this address: https://plateeditor.sourceforge.io - The source code is also available on GitHub, visit: https://github.com/vindelorme/PlateEditor More information about the source code and the API are available there (the wiki is still under construction, thanks for your patience!) For a list of recent updates, visit: https://sourceforge.net/p/plateeditor/wiki/Updates/ Hoping PlateEditor will make your life easier in the lab! If yes, please cite us: https://doi.org/10.1371/journal.pone.0252488

A toolkit of Python software useful in a laboratory data acquisition and analysis environment. Includes support for such protocols as VXI-11 (and its extension, LXI), Vernier LabPro (now very old), and National Instruments DSTP (now very old). Also includes data analysis and modelling tidbits. Python3 updates are on the way in the very near future for the biggest packages. the vxi11 package is fully up-to-date, although see the blog post about python 3.13