Search Results for "gnu/linux"

mzMatch is a Java collection of small commandline tools specific for metabolomics MS data analysis. The tools are built on top of the PeakML core library, providing mass spectrometry specific functionality and access to the PeakML file format.

Mass-Up is an Open-Source mass spectrometry utility for proteomics designed to support the preprocessing and analysis of MALDI-TOF mass spectrometry data. Mass-Up includes several tools and operations to load, preprocess and analyze MALDI-TOF data.

Maui is the Maltcms User Interface, a rich client application for Chromatography-Mass Spectrometry and related research areas.

Bioinformatics related demos and tutorials using the R programming language for large biological data. Licence: Creative Commons Attribution-NonCommercial 4.0 International License

...It integrates post-processing tool of protein identification and advanced statistical algorithms to process the MS/MS signals generated from the peptides labeled by isobaric tags for quantification. IQuant can run from a graphical user interface (GUI) as well as a command-line interface and work with both Windows and Linux system. This website contains the IQuant software, an example data labeled by iTRAQ-8plex for testing and a user's manual. If you have any question about IQuant, please contact me: wenbo@genomics.cn. The source code of IQuant can be found here "https://sourceforge.net/p/iquant/code/".

RMol is an R script with a collection of functions to link information of SD/Molfile structure databases with powerful graph analysis packages in R.

Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.

Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.

We use R (www.r-project.org) in order to generate a greater specificity and sensitivity of protein identification by Mass Spectrometry. These functions are implemented as add-on packages to the open source GPL software R.