Speaker
Report on the experience (or the proposed activity). It would be very important to mention key services which are essential for the success of your activity on the EGEE infrastructure.
The biological community is increasingly taking advantage of the
informatics
tools available. However informatics training is still scarce in
biology courses. In
our experience in porting protein structure prediction
applications in a grid
environment, the main difficulty we encountered was in being able
to formalize
job description and submission as well as output retrieval
through the use of
grid middleware. Essential to our experience was the integration
of our
applications within the GENIUS portal which allows job submission
and
management through the use of a user friendly grid interface.
This allows non
grid-trained users to profit from the advantages provided by the
grid
infrastructure.
Describe the scientific/technical community and the scientific/technical activity using (planning to use) the EGEE infrastructure. A high-level description is needed (neither a detailed specialist report nor a list of references).
In nature there exists only a tiny fraction of all the
theoretically possible protein
sequences. It is thus of interest for the biologists to study the
properties of
proteins not present in nature (the "never born proteins") as a
way to improve
our knowledge on the fundamental properties that make existing
protein
sequences so unique. Protein structure prediction tools combined
with the use
of large computing resources allow to tackle this problem.
Describe the added value of the Grid for the scientific/technical activity you (plan to) do on the Grid. This should include the scale of the activity and of the potential user community and the relevance for other scientific or business applications
The study of never born proteins requires the generation of a
large library of
protein sequences not present in nature and the prediction of
their three-
dimensional structure. This is not trivial when facing 10^5-10^7
protein
sequences. Indeed, on a single CPU it would require years to
predict the
structure of such a large library of protein sequences. On the
other hand, this is
a trivial parallelism problem in which the same computation (i.e.
the prediction
of the 3D structure of a protein sequence) must be repeated
several times (i.e.
on a large number of protein sequences). The use of the GRID
infrastructure
makes feasible to approach this problem in an acceptable time frame.
In addition, once the simulation in a grid environment has been
set up, the
same approach can be used to tackle problems of immediate biomedical
relevance such as the prediction of the structure of the entire
set of proteins of
a virus or a bacterial pathogen.
With a forward look to future evolution, discuss the issues you have encountered (or that you expect) in using the EGEE infrastructure. Wherever possible, point out the experience limitations (both in terms of existing services or missing functionality)
According to our experience, a simplified approach to the use of
grid resources
will be the key point to attract new communities, especially as
far as the
biomedical community is concerned. From this viewpoint, the further
development of web-based, user friendly services will be critical
to allow the
access of non informatics trained scientists to grid resources
and for the
success of grid computing approach.
