Bootcamp I: Absolute beginners

This bootcamp is aimed at participants using MaxQuant and Perseus for the first time and who need additional supervised practice and clarifications. The goal is to make sure that all participants are brought to the same level of understanding and can follow at the same pace as more experienced users. During this session the participants will have the opportunity to ask specific questions on the exercises from the tutorials. Any exercise steps, parameters and concepts brought up by the participants will be explained in detail.

Bootcamp II: Paleo proteomics

The analysis of ancient proteins from archaeological and paleontological samples requires the implementation of dedicated solutions. Ancient proteins are fragmented and chemically modified due to spontaneous, non-enzymatic reactions occurring over extended time ranges in uncontrolled environmental conditions. They can originate from extinct organisms whose genome is not available, and they are frequently co-extracted together with environmental contaminants and proteins from environmental microorganisms. Specific strategies need to be implanted at peptide-spectra matching stage, to maximise ancient protein sequence reconstruction and to accurately characterise ancient protein damage. During this workshop we will describe, with how some of the functions available in MaxQuant can be used to fulfil specific needs of ancient protein analysis.

Bootcamp III: Machine learning

This bootcamp introduces users to the basics of machine learning and deep learning with short tutorial on how to implement them in Perseus and Python. Machine learning has several applications in the downstream analysis of proteomics data for example in classification of patient-derived samples based on their protein expression pattern, predicting sub cellular localization of proteins, and in predicting spectra intensities. Deep learning is recently gaining attention in proteomics for example in predicting de-novo sequences and spectra intensities and will likely find more applications in the future. Users will also get a quick overview on how to use SVM, RF, conventional neural network and recurrent neural network methods to predict spectra intensities. Example source code for the machine learning bootcamp can be found on https://github.com/faviobol/MQSS2018 and https://github.com/Shivanitiwary/MQSS2018

Bootcamp IV: Perseus plug-in programming

This bootcamp introduces users to the programming of customized activities in the Perseus software. It makes use of the plugin architecture of Perseus, which allows integrating self-written components into the computational framework. Any type of activity can be implemented as a plugin, from simple matrix processing activities to complex visualizations. Plugins are written in the C# programming language and follow a simple and straightforward interface structure. The inner workings of plugins are studied by examining several examples of standard Perseus plugins in detail. Furthermore, it will be demonstrated how new plugins are generated within the Visual Studio integrated development environment. Please note that this is an advanced course.

Further information and software requirements can be found on the PluginTutorial GitHub page.