IMPROVED ALGORITHMS AND TOOLS FOR THE IDENTIFICATION OF NOVEL PROTEOFORMS USING TOP-DOWN PROTEOMICS

University of Tübingen
Faculty of Mathematics and Science
Germany Not US or Canada Tuebingen
protrein.eu/call-for-applicants/

Description

Implementation of sensitive and specific protein species identification and characterization for targeted and untargeted proteomics study by leveraging recently introduced mass deconvolution algorithms. Application of the developed algorithm to reveal novel proteoforms. Both algorithmic and machine learning-based approaches will be applied for an efficient and sensitive proteoform identification method. The developed algorithm will be used in a stand-alone tool as well as in an interactive visualization tool. The algorithm also could be embedded in instruments for better data acquisition. The development will be performed as part of OpenMS the major C++ open-source framework for computational proteomics. The expected results include i) tools implementing millisecond order of runtime per spectrum and increased proteoform identification rates at a given false-discovery rate and ii) application of these tools to large-scale proteomics data to identify novel proteoforms.


Qualifications

A strong background in algorithm.
Good software engineering skills. Ideally knowledge of the C++ and C# programming language.
Git-based version control system. If available, please provide a link to e.g. your GitHub account and/or link to past projects in your application.
Ideally, a background in statistics
Ideally, knowledge of (computational) mass spectrometry.
Strong command of English.


Start date

As soon as possible

How to Apply

protrein.eu/call-for-applicants/