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Open-source software for mass spectrometry
Showing 3 of 3 projects. Click any project card for scope, mentors, and proposal studio.
Mentors: Student: Tarush Singh
This project aims add support for new data formats of ion mobility-mass spectrometry data. Data from additional formats shall be read into the MZmine software using the existing data structures. A Java wrapper package will be developed using Java Native Access to harness the functionality of libraries Provided by vendor in specific binary formats, which can be utilized for accessing the internal structures. The primary target is the Waters .raw data format.
Mentors: Student: Suraj Verma
<p>MZmine is an open-source computer application written primarily in Java, used for data processing of mass-spectrometry data. The application supports various features related to LC-MS, like raw data import/export, peak-detection, statistical analysis tools and data visualization. The project aims at adding support for mzTab-m file format for MZmine3 which is standard file for result representation of LC-MS data after analysis. Further, CliqueMS feature annotation algorithm will be implemented in Java and associated GUI will be developed in this project.</p>
Mentors: Student: Łukasz Fiszer
<p>Mass spectrometry is an important analytical technique that allows to determine molecular composition of samples by obtaining mass spectra of ionized molecules.</p> <p>In this project I am going to develop a new module for automatic mass calibration that aims to reduce systematic error of measurement by shifting features to better match with predicted compounds. The calibration will give more accurate and easier to work with data, and is crucial to reduce false positives in molecular identification.</p> <p>I am also going to develop deisotoping support using high-resolution of mass spectra. Recent developments allow to obtain mass spectra of resolution high enough to observe differences of nuclear binding energies among isotopes. The new module I am going to build will detect isotopic patterns of chemical compounds and relate fine mass peaks with each other based on m/z differences corresponding to nuclear mass defects of isotopes of selected elements. The project will, among others, help annotate molecular formulas, improve and simplify downstream analysis and also be a software part visualizing the evidence supporting relativity (by incorporating binding energies into molecular prediction).</p>