Search Results for "image analysis algorithm"

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...

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.

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.

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.

Tigris is an open source suite of classes and programs implemented in C++ for single particle electron microscopic image processing.

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.

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.