December 12, 2014, Montreal.
If you are interested in travel support, send us an email.
In the past few years, the field of
molecular biology of the brain has been transformed from
hypothesis-based experiments to high-throughput experiments. The
massive growth of data, including measures of the brain
transcriptome, methylome and proteome, now raises new questions
in neurobiology and new challenges in analysis of these complex
and vast datasets. While many of these challenges are shared
with other computational biology studies, the complexity of the
brain poses special challenges. Brain genomics data includes
high-resolution molecular imagery, developmental time courses
and most importantly, underlies complex behavioral phenotypes
and psychiatric diseases. New methods are needed to address
questions about the brain-wide, genome-wide and life-long
genomic patterns in the brain and their relation to brain
functions like plasticity and information processing.
The goal of the workshop is to bring
together people from the neuroscience, cognitive science and the
machine learning community. It aims to ease the path for
scientists to connect the wealth of genomic data to the issues
of cognition and learning that are central to NIPS, with an eye
to the emerging high-throughput behavioral data which many are
gathering. We invite contributed talks on novel methods of
analysis to brain genomics, as well as techniques to make
meaningful statistical relationships to phenotypes.
The target audience includes two main groups: people interested
in developing machine learning approaches to neuroscience, and
people from neuroscience and cognitive science interested in
connecting their work to brain genomics.