RECOMB-AB aims to discuss recent
advances and present open algorithmic
problems in different areas of life
sciences. Today, life sciences are
in the midst of a major paradigm shift
driven by computational
sciences. RECOMB-AB emphasizes that this
is a two-way street: while
life sciences have greatly benefited
from new computational ideas,
they also are a major source of new open
problems and inspiration for
computational sciences. RECOMB-AB brings
together leading researchers
in the mathematical, computational, and
life sciences to discuss
interesting, challenging, and
well-formulated open problems in
algorithmic biology.
Many areas of computational sciences
started as an attempt to solve
applied problems and later became more
theoretically-oriented. These
theoretical aspects may be very valuable
even if they stray away from
the applied problems that originally
motivated them. Thus, RECOMB-AB
is interested in a wide range of
well-formulated open problems. Some
of them may be rather theoretical and
have limited biological
application. The solutions of others
might provide valuable tools for
biologists or might lead to new
biological discoveries. This blend of
theoretical and applied problems is a
fascinating feature of
algorithmic biology.
The discussion panels at RECOMB-AB will
also address the worrisome
proliferation of ill-formulated
computational problems in
bioinformatics. While some biological
problems can be translated into
well-formulated computational problems,
others defy all attempts to
bridge biology and computing. This may
result in computational biology
papers that lack a formulation of a
computational problem they are
trying to solve. While some such papers
may represent valuable
biological contributions (despite
lacking a well-defined computational
problem), others may represent
computational "pseudoscience."
RECOMB-AB will address the difficult
question of how to evaluate
computational papers that lack a
computational problem formulation.
Open problems should address a problem
of interest in Biology, whose
solution may depend on development of
new ideas in Computing, or
problems of interest in Computing that
were initially motivated by
Biology. Open problems may be completely
new; they may be problems
that were studied in the past but
without a precise formulation as an
algorithmic problem; or they may be new
and improved self-contained
formulations of previously published
problems.
