AG Fufezan
Schlossplatz 8 48143 Münster
Tel.: +49 251 83-24861
Fax: +49 251 83-28371 Sprechstunde: Mo. 11-12
@ Schlossplatz 8, R105
matched isotope pattern chromatogram
Clustering of protein translation profiles
LC MS/MS alignmet




pymzML is an extension to Python that offers
  • easy access to mass spectrometry (MS) data that allows the rapid development of tools,
  • a very fast parser for mzML data, the standard in mass spectrometry data format
  • a set of functions to compare or handle spectra

Project websites are:
>>> Bioinformatics publication
>>> WebSite
>>> source on Github


Ursgal, universal Python module combining common bottom-up proteomics tools for large-scale analysis


Lukas P. M. Kremer, Johannes Leufken, Purevdulam Oyunchimeg, Stefan Schulze and Christian Fufezan

Project websites are:
>>> JPR publication - Editors choice
>>> WebSite
>>> source on Github
Travis CI status Documentation Status Join the chat at


High throughput quantitative analysis of mass spectrometry data requires algorithms that allow fast and exact quantification of substances. pyQMS is such an algorithm based on the Python scripting language, thus can easily be incorporated in other workflows/programs.


J. Barth, A. Niehues and C. Fufezan

manuscript in prep


python module that allows sophisticated clustering of omics data.


D. Jaeger and C. Fufezan

Project websites are:
>>> Bioinformatics publication accepted
>>> WebSite
>>> source on Github


PiqDB is a NoSQL DB and thus allows efficient horizontal scaling for fast and complex queries on very large data sets using map reduce. Additionally, piqDB includes the distributed computing platform W13 (AK Fufezan, unpublished) that allows multi-host multi-cpu/core execution of Python scripts. Piqdb comprises a series of Python scripts that allow seamless integration of MS identification and quantification data. Similar to SuperHirn, piqDB allows alignment of large number of LC-MS/MS runs to be performed. In fact every experiment injected into piqDB can be used to redefine the master peptides that are used for the alignment procedure.


J. Barth and C. Fufezan

beta stage


p3d was developed in order to offer a Python module that is powerful and fast, yet intuitive to use. The simplicity of p3d is due to

  • the usage of object oriented programming (i.e. atoms are treated as vectors),
  • the implementation of a query parser that translates queries readable by humans into a combination of algebra set operations
  • the fact that no additional Python packages are necessary.

The speed is due to the usage of a binary space partitioning (BSP) tree which allows very fast queries in 3D (Henry et al. 1980). The additional synergy is obtained by the flexible combination of both speed and complexity in the queries to the structural data. The combination of these factors makes p3d the optimal module to rapidly develop new and powerful bioinformatic tools that follow the Python philosophy of making the source code readable.

Project websites are:
>>> BMC Bioinformatics publication
>>> WebSite
>>> source on Github

Impressum | © 2010 Institut für Biologie und Biotechnologie der Pflanzen
AG Dr. C. Fufezan
Schlossplatz 8 · 48143 Münster
Tel.: +49 251 83-24790 · Fax: +49 251 83-28371