Open Source MATLAB Information Analysis Software

LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.

The purpose of this program is to teach a computer to classify plants via their leaves. You just need to input the image of a leaf(acquired from scanner or camera), then the computer can tell you what kind of plant it is.

Source code from the Research Institute for Signals, Systems and Computational Intelligence http://fich.unl.edu.ar/sinc

NSB entropy and mutual information estimator; applications to the analysis of neural code.

C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.

Yet Another Audio Feature Extractor is a toolbox for audio analysis. Easy to use and efficient at extracting a large number of audio features simultaneously. WAV and MP3 files supported, or embedding in C++, Python or Matlab applications.

CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.

An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.

The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.

This is a MATLAB toolbox for the quality control and scoring of EMAP and SGA genetic interaction data. It includes a graphical user interface and some automatic plot-generating tools.

BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.

Tools for mass spectrometry, especially for protein mass spectrometry and proteomics: Quantification tools, converters for Applied Biosystems (Q Star and Q Trap), calculation of in-silico fragmentation spectra, converter for Mascot result files

This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying densities that would otherwise impossible had the same algorithm been applied to the unscaled dataset. Reference: Zhu, Y., Ting, K. M., & Carman, M. J. (2016). Density-ratio based clustering for discovering clusters with varying densities. Pattern Recognition. http://www.sciencedirect.com/science/article/pii/S0031320316301571

Load data from an axoscope abf file in matlab.

Framework for uncertainty propagation in predictive models targeted for collaborative science

MATLAB Audio Database Toolbox enables easy access and filtering of audio databases such as TIMIT and YOHO by their metadata. The database toolbox comes to replace the manual filtering and custom coding usually required for accessing such databases.

This software calculates the mass-based dissimilarity matrix for data mining algorithms relying on a distance measure. References: Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. KDD 2016 http://dx.doi.org/10.1145/2939672.2939779 The source code, presentation slide and poster are attached under "Files". The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed under the Gnu General Public license GPLv3, any derivative work must be licensed under the GPL as well. This software is free only for non-commercial use. For commercial projects, it is possible to obtain a commercial license through the Commercial Services of Federation University Australia. Please email the first author of the original paper tingkm@nju.edu.cn for any inquiries about this software.

SPIW is a MATLAB toolbox, for automated processing of scanning probe microscope images. Tools are applicable to all SPM images, but the main focus is on images with atomic or molecular resolution. SPIW is primarily a MATLAB toolbox with functions designed to be called in a user's own script. SPIW also has a very basic GUI for browsing and exporting images. For information on SPIW's performance see our publication ( http://dx.doi.org/10.1063/1.4827076 ) in the Review of Scientific Instruments. A related open-source project SPIEPy (https://pypi.python.org/pypi/SPIEPy/) is developing a python library to for automated SPM imaged enhancement. SPIEPy brings many SPIW algorithms to the Python user.

This is a Matlab software package for single molecule FRET data analysis.

Version 1.1 is no longer supported. Please see the new version at https://usc-imi.github.io/aeo-light/ Description for 1.1 continues below: AEO-Light 1.1 is an open-source software application that takes a digital scan of motion picture film with optical sound tracks and directly reproduces the audio, producing as a result a synchronized sound film file. Funded by a grant from the National Endowment for the Humanities and by the University of South Carolina.

Bayesian Surprise Matlab toolkit is a basic toolkit for computing Bayesian surprise values given a large set of input samples. It is also useful as way of exploring surprise theory. For more information see also: http://ilab.usc.edu/

KYM is a MATLAB / GNU Octave set of functions that implements a wavelet-based automated procedure of quantification and characterization of biological signals. In particular it has been thought for the analysis of the oscillatory component of cytosolic calcium concentration time course.

Unix-based preparation and analysis toolbox for Nanomaterials and Room Temperature Ionic Liquids in Bulk and Slab using bash scripts, Gromacs tools and Matlab functions. NaRIBaS provides a framework that decouples user input parameter and terminal based command lines. NaRIBaS does not replace a simulation software and specific analysis tools like Gromacs, but it allows iterative repetition of tasks while changing specific input parameter. The toolbox is to be understood as a scripting framework rather than a black-box software. Task specific input and preparation or analysis function, are easy expandable to meet the scientific characteristic of constant changing properties. Concepts for efficiently storing and analysing large files in conjunction with graphical visualization and numerical data processing are presented in a Manual. A documented script collection that allows reproducing all simulations and analysis results presented in the Doctoral thesis of the author.

The OARS app is a data logger developed to run on Android OS and devices containing an internal GPS ,along with micro-electro-mechanical systems (MEMS) chipset. Specifically the Invensence MPU-6000 or newer. This chip is a highly accurate inertial measurement unit, or (IMU). Contained within this small IMU is a 3-axis Accelerometer, 3-axis Gyro, and 3-axis Magnetometer. Along with a built in processor, it can calculate movements along 9-axis. Depending on platform and app setting, OARS can record sensor values at a rate up to 100hz, or 100 positions per second. GPS data such as Longitude, Latitude, Direction, Speed, and Elevation, are also logged at approximately 1hz, or 1 update per second. Giving you the ability to precisely map an equipped objects location, orientation, and rate of movement along any plane with extreme accuracy.