The Exelixis Lab


Enabling Research in Evolutionary Biology

Our Mission - Enable Research in Evolutionary Biology

Our focus is on the evolution of hardware and parallel computer architectures as well as on the evolution of molecular sequences.

We understand Bioinformatics as a discipline that develops algorithms, models, and tools that help Biologists to generate new biological insights and knowledge. We try to bridge the gap between the world of systematics and the world of high performance computing.

Due to the increasing descrepancy between the pace of molecular data accumulation and increase in CPU speeds (which is much slower), which we call the "Bio-Gap" we feel that the time has come to establish parallel computing as standard technique in Bioinformatics.

New Software

ExaBayes: Large Scale and Massively Parallel Bayesian Phylogenetic Inference

ExaBayes: A fast and scalable Bayesian inference tool for normal computers and supercomputers.

It is as fast or faster (on DNA data) than MrBayes and we demonstrated parallel scalability of up to 32,000 cores for it on the Munich supercomputing system: SuperMUC.

For more details, please visit the ExaBayes page.

RAxML

The latest version of RAxML can be found at Alexis github repository.

RAxML questions, help & bug reports: please use the RAxML google group

There is finally a new manual available for RAxML version 8.0.X. You can get it here

Students from KIT

We are always looking for student programmers (HiWis) and students interested in doing bachelor/master theses projects with us. If you are interested please send an email to Alexis at Alexandros dot Stamatakis at h hyphen its dot org

New Papers

Our 5 Most Recent Papers

  1. A.J. Aberer, K. Kobert, A. Stamatakis: "ExaBayes: Massively Parallel Bayesian Tree Inference for the Whole-Genome Era". In Molecular Biology and Evolution, 2014, open access.
  2. K. Kobert, T. Flouri, A.J. Aberer, A. Stamatakis: "The divisible load balance problem and its application to phylogenetic inference". In Proceedings of WABI 2014, Wroclaw, Poland, September 2014, accepted for publication. PDF
  3. T. Flouri, K. Kobert, S.P. Pissis, A. Stamatakis: "An optimal algorithm for computing all subtree repeats in trees". In Phil. Trans. R. Soc. A 372:2016, 2014, open access.
  4. R. Lanfear, B. Calcott, D. Kainer, C. Mayer, A. Stamatakis: "Selecting optimal partitioning schemes for phylogenomic datasets". In BMC Evolutionary Biology 14:1, 82, 2014, on-line access.
  5. R.S. Peters, K. Meusemann, M. Petersen, C. Mayer, J. Wilbrandt, T. Ziesmann, A. Donath, K.M. Kjer, U. Aspöck, H. Aspöck, A. Aberer, A. Stamatakis, F. Friedrich, F. Hünefeld, O. Niehuis, R.G. Beutel, B. Misof: "The evolutionary history of holometabolous insects inferred from transcriptome-based phylogeny and comprehensive morphological data". In BMC Evolutionary Biology, 14:52, 2014, on-line access.
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