Search Results for "image analysis algorithm"
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Showing 11 open source projects for "image analysis algorithm"
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis... -
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Nest-o-Patch
Software for analysis of patch-clamp recordings and other wave data
This program was designed mainly for preconditioning and analysis of electrophysiological data, including patch-clamp and 2-electrode voltage clamp recordings. The program includes tools both for basic analysis of whole-cell recordings or analysis of single channel properties. Program can display and analyse long traces incuding many sweeps, series and even groups simultaneously. Current amplitudes or time intervals are easily measured. Single channel conductance, kinetics, NPo, as well as... -
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coDDMaker
distributions and co-distribution 2D signal analysis
coDDMaker is a MATLAB® App Designer's software program for the guided analysis of the distributions and co-distribution of marker pairs in 2D image. -
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DDMaker
Local Distribution Density Map Maker
DDMaker perform local density analysis and generates pseudocolor maps of the spatial distribution of imaged cellular structures in 2D images, starting from either RGB color, grey level or binary images. DDMaker local density analysis permit to selectively denoise the signal, visualize and quantify its distribution and threshold the image basing on local density. -
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ModST
A tool to search post-translational modifications in a blind mode
ModST (pronounced as modest) is a tool to search post-translational modifications (PTMs) in mass spectrometry data in an unrestrictive manner. It can search for hundreds of modification without any user provided information for variable modifications. Due to data level parallelization implemented through perl it is fast, portable and easy to use to identify and analyse PTMs in MS/MS data. -
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sdmixer
A tool for 2D/ 3D multi-color super resolution microscopy
The open source software sdmixer reconstructs a TIFF image from a single molecule localization data set. The spectral demixing option allows multi color super resolution microscopy. sdmixer supports multipage TIFF images and is able to process large 3D data sets. Further features are 2D/3D convolution, histogram based contrast enhancement and nearest neighbor analysis. -
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This package includes a collection of MATLAB files which are designed to: 1. Given a calibration scan of the image of a point emitter with an engineered point spread function (PSF), 2. Perform a phase retrieval algorithm based on maximum likelihood estimation (MLE) of a phase aberration term which is added to the theoretical pupil function of the imaging system. 3. Use the phase-retrieved pupil function to perform single-emitter localization.
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MORPHE
MORphological PHenotype Extraction
MORphological PHenotype Extraction (MORPHE) is a suite of automated image processing, visualization, and classification algorithms to facilitate the analysis of heritable and clonal red-to-green transitions that occurred during the growth of a colony. -
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Tigris is an open source suite of classes and programs implemented in C++ for single particle electron microscopic image processing.
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SPADE
A toolkit for developing and deploying protein structure algorithms.
The Structural Proteomics Application Development Environment is a Python tool kit for developing and deploying bioinformatics applications. Handles graphics, analysis, and modeling of protein sequence and structure. Source and Win installers available. SPADE source code can be cloned from http://www.github.com/deaconjs/SPADE. -
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PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
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