Open Source MATLAB Information Analysis Software

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

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

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.

Load data from an axoscope abf file in matlab.

This project houses software to analyze data acquired from electrophysiology experiments. Currently, we have an Octave/MATLAB program to analyze electroneurogram traces of coupled oscillators, and a Perl library for the analysis of voltage trace data

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

Visualization and clustering analysis of X-Ray diffraction data from combinatorial thin film libraries.

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

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.

The main goal of this project is to develop new algorithms of machine learning and collect examples of existing methods. This collection pursues scientific and educational purposes.

Audio spectrum analyzer in software module and a hardware module to display the spectrum.

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.

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/

This is the prototype version of software for robust detecting and segmentation of cell nuclei in 3D fluorescence labeled microscopy images. First release coming soon...

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.

Framework for uncertainty propagation in predictive models targeted for collaborative science

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 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

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.

Functional Mechanism is a differentially private method designed for a large class of optimization-based analyses. The main idea is to enforce epsilon-differential privacy by perturbing the objective function of the optimization problem, rather than its results. Please cite the following paper if you choose to use this code: J. Zhang, Z. Zhang, X. Xiao, Y. Yang, and M. Winslett. Functional Mechanism: Regression Analysis under Differential Privacy. PVLDB 5(11):1364-1375, 2012.

Please refer to the original article published in PLOS ONE at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0049386. GUItars's user-friendly graphical interface enables rapid analysis of RNAi and small molecule screens. GUItars uses SSMD for hit selection, which is preferred for its ability to diminish sample size effects and the false hit rate, making it superior to other widely used HTS analysis methods. The program can handle the analysis for screens without replicates as well as with replicates. For comparison purposes, non-SSMD-based methods such as percent activity, z-score, and t-test are also provided as scoring options. Version 2.1 released: several bugs fixed. Version 3.0 released for Windows and Mac: experiment-wise analysis option, map to all samples option (no hit cut-off needed), percent activity for replicates option and .ai output format are added

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.

math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net

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.

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.