|| School of Computer and Communication Sciences
|| Laboratory for Computational Biology and Bioinformatics
|| EPFL > IC > LCBB
Laboratory for Computational
Biology and Bioinformatics
The Laboratory was started in June 2006 by Professor Bernard Moret. Our main area
of interest is the design of models and algorithms for problems arising in
biology, mostly evolutionary biology (phylogenetics) and genomics
(regulatory, comparative, and evolutionary genomics). We work mainly with
large-scale simulations, but we also make use of published data, including
most common databases in genomics and proteomics.
The Laboratory closed at end of 2016, as Prof. Moret retired (after 36.5 years as a faculty member, first at the
University of New Mexico, then at EPFL).
To celebrate the achievements of lab members and collaborators, and to thank major sources of inspiration, a 2-day scientific meeting, CLIMB (Colloquium on aLgorithms in Molecular Biology), took place in Lausanne on Nov. 7-8, 2016, organized by lab members Daniel Doerr and Min Ye.
A second event, organized by Profs. Tandy Warnow (UIUC) and Satish Rao (UC Berkeley) and focussed more on Professor Moret and his area of research, will take place in Berkeley (in Soda Hall) on June 2, 2017.
To design, implement, test, and assess models and
algorithms for discrete problems arising in evolutionary molecular
See the 2011 ACM Ubiquity interview with Prof. Moret on Experimental Algorithmics.
We regularly teach the Master's level courses Computational
Molecular Biology (Spring semesters, 5 EPFL credits) and Advanced
Algorithms (Fall or Spring semesters, 7 EPFL credits).
We occasionally teach the Bachelor's level course Theoretical Computer Science, the Master's level course Computational Geometry
and the PhD level course Theory of Computation (5 EPFL credits).
We have co-taught (with colleagues from the School of Life Sciences) courses in
Bioinformatics at both Master's and PhD level.
EPFL is consistently ranked among Europe's top 5 (along with Cambridge and Oxford, Imperial College, and its sister institution ETHZ) and among the world's
top 20 in Engineering and Computer Science; see, for instance,
Keep in mind that most of these rankings vary widely from year to year and tend to promote geographic diversity at the expense of quality (with the result that fewer US universities appear at the top than should really be the case); some are also quite biased in favor of institutions in their own region. The cumulative effect for EPFL, however, is clear.
Note that (unsurprisingly in view of the poor design of its web site and its insufficient use of English) EPFL fares poorly in the two standard rankings based on results from web searches, the Ranking Web of Universities overall (#10 / #73) and the World University Web Ranking overall (#22 / #138).