DREAMTools

UNLABELLED: DREAM challenges are community competitions designed to advance
computational methods and address fundamental questions in system biology and
translational medicine. Each challenge asks participants to develop and apply
computational methods to either predict unobserved outcomes or to identify
unknown model parameters given a set of training data. Computational methods are
evaluated using an automated scoring metric, scores are posted to a public
leaderboard, and methods are published to facilitate community discussions on how
to build improved methods. By engaging participants from a wide range of science
and engineering backgrounds, DREAM challenges can comparatively evaluate a wide
range of statistical, machine learning, and biophysical methods. Here, we
describe DREAMTools, a Python package for evaluating DREAM challenge scoring
metrics. DREAMTools provides a command line interface that enables researchers to
test new methods on past challenges, as well as a framework for scoring new
challenges. As of March 2016, DREAMTools includes more than 80% of completed
DREAM challenges. DREAMTools complements the data, metadata, and software tools
available at the DREAM website http://dreamchallenges.org and on the Synapse
platform at https://www.synapse.org. AVAILABILITY: DREAMTools is a Python
package. Releases and documentation are available at
http://pypi.python.org/pypi/dreamtools. The source code is available at
http://github.com/dreamtools/dreamtools.

DREAMTools: a Python package for scoring collaborative challenges.

DREAMTools provides algorithms to score DREAM challenges and assess new methods on past DREAM challenges.

DREAMTools

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