Open Source MATLAB Information Analysis Software
Sort By:
MATLAB Information Analysis Software
View 201 business solutionsBrowse free open source MATLAB Information Analysis Software and projects below. Use the toggles on the left to filter open source MATLAB Information Analysis Software by OS, license, language, programming language, and project status.
-
AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
-
The Most Powerful Software Platform for EHSQ and ESG ManagementChoose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
-
1
LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
2
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.
-
3
Source code from the Research Institute for Signals, Systems and Computational Intelligence http://fich.unl.edu.ar/sinc
-
4
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.
-
Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
-
5
-
6
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
-
7
-
8
-
9
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.
-
B2i offers full-service IR websites, widgets and pluginsB2i Technologies provides the most robust and versatile tools to manage your Corporate website, Investor Relations website and email communications. Our Investor Relations Software solutions work through automation and implements into existing systems with ease in only a few steps. Our solutions not only help you stay compliant but save valuable time while reporting and delivering critical financial data and press release activities to investors. B2i's Investor Relations Solution provides highly reliable and customizable data for corporate websites including press releases, stock data, charting, and SEC filings within SOX compliance standards. Our investor relations software displays real-time data on your website without requiring additional work on your behalf. Once you have completed your filings and press releases they are automatically loaded onto your website and formatted for easy access.
-
10
gfit creates an interface between computational models and experimental data and provides tools for their analysis
-
11
matImage
An image processing and analysis library for Matlab
MatImage is a Matlab library for image processing and analysis in 2D and 3D. It contains more than 250 fonctions for image enhancement, filtering, analysis, or visualisation, as well as for creating basic test shapes. It is built as a complement of the Mathworks image processing toolbox (IPT). Project is being transfered to GitHub: http://github.com/dlegland/matImage -
12
AEO-Light 1.1
Version 1.1 is no longer supported.
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. -
13
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.
-
14
-
15
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.
-
16
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/
-
17
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...
-
18
Visualization and clustering analysis of X-Ray diffraction data from combinatorial thin film libraries.
-
19
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.
-
20
-
21
Density-ratio based clustering
Discovering clusters with varying densities
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 -
22
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.
-
23
Functional Mechanism
Regression Analysis under Differential Privacy
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. -
24
GUItars
GUItars is designed for the analysis of high throughput RNAi data.
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 -
25
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.
