DREAMTools: a Python package for scoring collaborative challenges

  1. Cokelaer, Thomas
  2. Bansal, Mukesh
  3. Bare, Christopher
  4. Bilal, Erhan
  5. Bot, Brian M.
  6. Chaibub Neto, Elias
  7. Eduati, Federica
  8. de la Fuente, Alberto
  9. Gönen, Mehmet
  10. Hill, Steven M.
  11. Hoff, Bruce
  12. Karr, Jonathan R.
  13. Küffner, Robert
  14. Menden, Michael P.
  15. Meyer, Pablo
  16. Norel, Raquel
  17. Pratap, Abhishek
  18. Prill, Robert J.
  19. Weirauch, Matthew T.
  20. Costello, James C.
  21. Stolovitzky, Gustavo
  22. Saez-Rodriguez, Julio

Download
f1000research-4-9054.pdf 2,32MB
WeightNameValue
1000 Titel
  • DREAMTools: a Python package for scoring collaborative challenges
1000 Autor/in
  1. Cokelaer, Thomas |
  2. Bansal, Mukesh |
  3. Bare, Christopher |
  4. Bilal, Erhan |
  5. Bot, Brian M. |
  6. Chaibub Neto, Elias |
  7. Eduati, Federica |
  8. de la Fuente, Alberto |
  9. Gönen, Mehmet |
  10. Hill, Steven M. |
  11. Hoff, Bruce |
  12. Karr, Jonathan R. |
  13. Küffner, Robert |
  14. Menden, Michael P. |
  15. Meyer, Pablo |
  16. Norel, Raquel |
  17. Pratap, Abhishek |
  18. Prill, Robert J. |
  19. Weirauch, Matthew T. |
  20. Costello, James C. |
  21. Stolovitzky, Gustavo |
  22. Saez-Rodriguez, Julio |
1000 Erscheinungsjahr 2016
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2016-04-08
1000 Erschienen in
1000 Quellenangabe
  • 4: 1030
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2016
1000 Lizenz
1000 Verlagsversion
  • https://dx.doi.org/10.12688/f1000research.7118.2 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837986/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Sacherschließung
lokal crowdsourcing
lokal machine learning
lokal systems biology
lokal DREAM
lokal benchmarking
lokal collaborative competition
lokal translational medicine
lokal method evaluation
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/Q29rZWxhZXIswqBUaG9tYXM=|https://frl.publisso.de/adhoc/creator/QmFuc2FsLMKgTXVrZXNo|https://frl.publisso.de/adhoc/creator/QmFyZSzCoENocmlzdG9waGVy|https://frl.publisso.de/adhoc/creator/QmlsYWwswqBFcmhhbg==|https://frl.publisso.de/adhoc/creator/Qm90LMKgQnJpYW4gTS4=|https://frl.publisso.de/adhoc/creator/Q2hhaWJ1YiBOZXRvLMKgRWxpYXM=|https://frl.publisso.de/adhoc/creator/RWR1YXRpLMKgRmVkZXJpY2E=|https://frl.publisso.de/adhoc/creator/ZGUgbGEgRnVlbnRlLMKgQWxiZXJ0bw==|https://frl.publisso.de/adhoc/creator/R8O2bmVuLMKgTWVobWV0|https://frl.publisso.de/adhoc/creator/SGlsbCwgU3RldmVuIE0u|https://frl.publisso.de/adhoc/creator/SG9mZizCoEJydWNl|https://frl.publisso.de/adhoc/creator/S2FycizCoEpvbmF0aGFuIFIu|https://frl.publisso.de/adhoc/creator/S8O8ZmZuZXIswqAgUm9iZXJ0|https://frl.publisso.de/adhoc/creator/TWVuZGVuLMKgTWljaGFlbCBQLg==|https://frl.publisso.de/adhoc/creator/TWV5ZXIswqBQYWJsbw==|https://frl.publisso.de/adhoc/creator/Tm9yZWwswqBSYXF1ZWw=|https://frl.publisso.de/adhoc/creator/UHJhdGFwLMKgQWJoaXNoZWs=|https://frl.publisso.de/adhoc/creator/UHJpbGwswqBSb2JlcnQgSi4=|https://frl.publisso.de/adhoc/creator/V2VpcmF1Y2gswqBNYXR0aGV3IFQu|https://frl.publisso.de/adhoc/creator/Q29zdGVsbG8swqBKYW1lcyBDLg==|https://frl.publisso.de/adhoc/creator/U3RvbG92aXR6a3kswqBHdXN0YXZv|https://frl.publisso.de/adhoc/creator/U2Flei1Sb2RyaWd1ZXoswqBKdWxpbw==
1000 Label
1000 Förderer
  1. National Science Foundation (NSF) |
  2. James S. McDonnell Foundation |
1000 Fördernummer
  1. -
  2. -
1000 Förderprogramm
  1. Graduate Fellowship
  2. Postdoctoral Award in Studying Complex Systems
1000 Dateien
  1. DREAMTools: a Python package for scoring collaborative challenges
    DREAMTools: a Python package for scoring collaborative challenges
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Science Foundation (NSF) |
    1000 Förderprogramm Graduate Fellowship
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer James S. McDonnell Foundation |
    1000 Förderprogramm Postdoctoral Award in Studying Complex Systems
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6404206.rdf
1000 Erstellt am 2017-08-28T12:15:02.793+0200
1000 Erstellt von 218
1000 beschreibt frl:6404206
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet 2020-12-09T13:30:55.276+0100
1000 Objekt bearb. Wed Dec 09 13:30:55 CET 2020
1000 Vgl. frl:6404206
1000 Oai Id
  1. oai:frl.publisso.de:frl:6404206 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source