The festschrift is now available online:
And in print:
We invite all interested scholars to contribute to a festschrift on the occasion of the retirement of Gaston Gonnet. We particularly welcome original papers and surveys in all areas of Prof. Gonnet's work, including (but not limited to) bioinformatics, symbolic and numeric computation, algorithms, text-mining, computational science, and high-performance computing.
We have partnered with PeerJ, an Open Access journal, to handle the submission process. All submissions will be first considered as preprints. For submissions that fall within PeerJ’s remit (original research papers in bioinformatics and computational science papers with a biology component), there will be the possibility of undergoing peer-review and, subject to acceptance under normal PeerJ's criteria, publication in their journal. Preprints are free and peer-reviewed articles incur a modest publication fee (but note that some institutions have special arrangements and submissions received before 31 March are free—see PeerJ’s website for more info).
Some of the contributions will be invited for oral presentation at the retirement symposium (on 4 July 2014 at ETH Zurich, Switzerland), but presence at the symposium in not required to contribute to the festschrift.
Please direct enquiries to Maria Anisimova (maria.anisimova at inf.ethz.ch) or Christophe Dessimoz (c.dessimoz at ucl.ac.uk).
More info on the symposium is available at http://gnome2014.lnk.ch.
All contributions should be submitted as a PeerJ PrePrint through the normal PeerJ website (http://www.peerj.com), indicating in the “Notes to Staff” field “Festschrift Gaston Gonnet”.
Once contributions are recorded as preprints, authors can choose to submit them for publication in the PeerJ journal (subject to their usual peer-review standards).
For contributions outside PeerJ’s remit (which is the biological, bioinformatics, computational biology, medical, and health fields), we will get in touch with the authors to find a publication solution on a case-by-case basis.