Computational Proteomics

Veit Schwämmle

Assistant professor
Protein Research Group
Department for Biochemistry and Molecular Biology
University of Southern Denmark
Email

Research

As a part of the Protein Research Group, I investigate post-translational modifications (PTMs) of proteins and their crosstalk. I am mostly interested in quantifying crosstalk and linking it to biological functions.
I apply statistical methods, develop algorithms and carry out simulations on the computer. With these methods, I analyze experimental data from protein mass spectrometry and integrate it with other -omics data sets.

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Software

Databases

Visit the CrosstalkDB hosting quantitative data for crosstalk between histone proteins measured by middle-down mass spectrometry.
The Elixir Tools and Data Service Registry, bio.tools, launched in January 2015, aims to build a comprehensive gateway to databases and tools for Life Science data analysis.

Shiny apps

The Shiny framework facilitates embedding R-scripts into simple GUIs.
Some of my developments are now available as simple web applications (see Shiny Apps)

R scripts

The scripts carrying tasks such as fuzzy c-means clustering with full parameter estimation can be downloaded at from the institute's website.

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My main research focuses on the study of post-translational modifications and chromatin. I am mostly interested in deciphering the complex behaviour and the biological consequences of crosstalk between these modifications. With my background in theoretical physics and computational modeling, I use methods adapted from statistical physics, bioinformatics, and general computer modeling approaches which I already applied to study physical, biological and linguistic systems. During the last years, I moved to the proteomics field and developed algorithms and bioinformatic tools to improve the analysis of data coming from large-scale proteomics experiments.
For my publication record, see Google Scholar.

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Chromatin Biology
  • Middle-down mass spectrometry We developed a workflow to quantify PTMs on histone tails (refs).

  • CrosstalkDB With quantitative data from middle-down and top-down mass spectrometry, the web server collects and analyzes the input files, followed by statistical assessment of the crosstalk between measured PTMs (refs).
    Access CrosstalkDB
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  • Computational models Taking simple rules for writing, propagating and deleting histone PTMs on chromatin, we were able to reproduce global patterns measured by ChIP-seq experiments. The implementation of crosstalk rules results in a rich spatial and temporal behavior (ref).

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Computational Proteomics

  • Review For an overview of methods used in PTMomics see (ref).

  • Characterization of crosstalk Large-scale estimation of crosstalk between nearby residues (ref). Interplay scores provide quantitative information about negative and positive crosstalk between PTMs on a peptide (ref).

  • Statistical tests The complexity of high-throughput mass spectrometry experiments often leads to low replicates numbers and many missing values, especially when measuring (un)modified peptides. We implemented a combination of statistical tests that yields statistical results with sufficiently high confidence (ref). Launch app

  • Pattern recognition Fuzzy c-means clustering is a popular algorithm to detect common expression profiles in noisy data. However, wrongly set parameter values often lead to biased results. Our work provides a simple way to estimate appropriate parameter values (ref). Launch app

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Complex Systems
  • Biological evolution See my former works on aging, sympatric speciation and competitive cellular automata (refs).

  • Simulations Almost anything can be simulated on the computer including sand dunes, opinion dynamics and linguistics (refs).

  • Statistical Mechanics See my works on generalized entropies and Fokker-Planck equations (refs).

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Data analysis of proteomics data

This course presents an overview of the main methods for analysis of data from peptide mass spectrometry and other -omics data.


Click on the picture for course material.

1st Year Bachelor Project

Functional analysis of a fish oil diet.


Click on the picture for course material.

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Automated fuzzy c-means clustering
Find the source code here.
Detection of differentially regulated features
Find the source code here.
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Elixir
(European Infrastructure for Biological Information)

The Danish node of the Elixir consortium implements and maintains the registry of software tools in life science (ref). The variety and complexity of such software makes its categorization by keywords or by hierarchical presentation difficult. The registry adapts a more flexible approach by basing software descriptions on EDAM ontologies. I am involved in several projects aiming to improve and extend curation of software tools, to create adapted workflows from the registry content, as well as to assess the internal structure of EDAM ontologies.
The 2nd Annual Danish Bioinformatics Conference
will take place in Odense in August.
Users:
We are grateful for feedback on the functionality and content of the registry.
Software developers:
We aim to provide a complete and up-to-date collection of software tools and therefore encourage software developers to

  • a) Check whether their software is already described

  • b) If yes, contact the maintainer for further curation and validation

  • c) If no, create an entry for their tool

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EuBIC
(EuPA Bioinformatics Initiative)

Initiative of young investigators in Europe to improve support and coordination of training and software development in proteomics bioinformatics.
Conference: We are organizing a conference and workshop on Computational Proteomics to be held in Semmering, Austria, in January. More details will be given shortly.

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