DREAM Challenges       

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DREAM Challenges - Publications by IBM DREAM Team


Saez-Rodriguez J, Costello J, Friend S, Kellen M, Mangravite L, Meyer P, Norman T, Stolovitzky G; Crowdsourcing biomedical research: leveraging communities as innovation engines; Nature Reviews Genetics; 17; 470–486 (2016) (doi:10.1038/nrg.2016.69)

Guinney J, Wang T, et. al.; Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data; The Lancet Oncology: (2016); (doi:10.1016/S1470-2045(16)30560-5)
Allen, G, et al;  Crowdsourced estimation of cognitive decline and resilience in Alzheimer’s disease; Alzheimer’s & Dementia 12 (2016) 645-653; (doi:10.1016/j.jalz.2016.02.006)

Cokelaer T, Bansal M, Bare C et al. DREAMTools: a Python package for scoring collaborative challenges [version 2; referees: 1 approved, 2 approved with reservations]. F1000Research 2016, 4:1030  (doi: 10.12688/f1000research.7118.2)
 
Noren DP, Long BL, Norel R, Rrhissorrakrai K, Hess K, et al. (2016) A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis. PLoS Comput Biol 12(6): e1004890. (doi: 10.1371/journal.pcbi.1004890)

Eduati F, Mangravite LM, et al; Prediction of human population responses to toxic compounds by a collaborative competition; Nature Biotechnology (2015) doi:10.1038/nbt.3299

Jonathan R. Karr, Williams A, Zucker J, et al; Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models; PLoS Comput Biol (2015) DOI: 10.1371/journal.pcbi.1004096

Ewing AD, Houlahan KE, et. al; Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.
Nat Methods. (2015) doi: 10.1038/nmeth.3407.

Abdallah K, Hugh-Jones C, Norman T, Friend S, Stolovitzky G.; The Prostate Cancer DREAM Challenge: A Community-Wide Effort to Use Open Clinical Trial Data for the Quantitative Prediction of Outcomes in Metastatic Prostate Cancer; Oncologist. (2015)  doi: 10.1634/theoncologist.2015-0054.

Boutros PC, Ewing AD, et al.; Global optimization of somatic variant identification in cancer genomes with a global community challenge.; Nat Genet. (2014)  doi: 10.1038/ng.2932.

Boutros PC, Margolin AA, Stuart JM, Califano A, Stolovitzky G.; Toward better benchmarking: challenge-based methods assessment in cancer genomics;. Genome Biol. (2014)  doi: 10.1186/s13059-014-0462-7.

Meyer, Pablo;  Cokelaer, Thomas;  Chandran, Deepak;  Kim, Kyung Hyuk;  Loh, Po-Ru et al.; Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach; BMC Systems Biology vol. 8 (1) p. 13 (2014) doi:10.1186/1752-0509-8-13

Robert Küffner , Zach N, Norel R, Hawe J, et al,; Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression, Nature Biotechnology (2014) doi:10.1038/nbt.3051

Mukesh Bansal, et. al; A community computational challenge to predict the activity of pairs of compounds; Nature Biotechnology,(2014) doi:10.1038/nbt.3052

James Costello , Heiser L, Georgii E, et al., A community effort to assess and improve drug sensitivity prediction algorithms; Nature Biotechnology (2014) doi:10.1038/nbt.2877

Robert M Plenge, Jeffrey D Greenberg, Lara M Mangravite, Jonathan M J Derry, Eli A Stahl, Marieke J H Coenen, Anne Barton, Leonid Padyukov, Lars Klareskog, Peter K Gregersen, Xavier Mariette, Larry W Moreland, S Louis Bridges Jr, Niek de Vries, Tom W J Huizinga, Henk-Jan Guchelaar, International Rheumatoid Arthritis Consortium (INTERACT), Stephen H Friend & Gustavo Stolovitzky; Crowdsourcing genetic prediction of clinical utility in the Rheumatoid Arthritis Responder Challenge; Nature Genetics 45,468-469 (2013) doi:10.1038/ng.2623

Bilal E, Dutkowski J, Guinney J, Jang IS, Logsdon BA, et al. (2013); Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling; PLoS Comput Biol 9(5): e1003047. doi:10.1371/journal.pcbi.1003047

Pablo Meyer, Geoffrey Siwo, Danny Zeevi, Eilon Sharon, Raquel Norel, DREAM6 Promoter Prediction Consortium, Eran Segal and Gustavo Stolovitzky; Inferring gene expression from ribosomal promoter sequences, a crowdsourcing approach: Genome Res 2013. 23: 1928-1937. doi:10.1101/gr.157420.113

Margolin, a. a. and Bilal, E.Huang, E. Norman, T. C. and Ottestad, L. and Mecham, B. H. and Sauerwine, B. and Kellen, M. R. and Mangravite, L. M. and Furia, M. D. and Vollan, H. K. M. and Rueda, O. M. and Guinney, J. and Deflaux, N. a. and Hoff, B. and and Schildwachter, X. and Russnes, H. G. and Park, D. and Vang, V. O. and Pirtle, T. and Youseff, L. and Citro, C. and Curtis, C. and Kristensen, V. N. and Hellerstein, J. and Friend, S. H. and Stolovitzky, G. and Aparicio, S. and Caldas, C. and Borresen-Dale, A.-L.; Systematic Analysis of Challenge-Driven Improvements in Molecular Prognostic Models for Breast Cancer; Sci. Transl. Med. 5, 181re1 (2013). doi:10.1126/scitranslmed.3006112

Weirauch, M. T., Cote, A., Norel, R., Annala, M., Zhao, Y., Riley, T. R., Saez-Rodriguez, J., Cokelaer, T., Vedenko, A., Talukder, S., DREAM5 Consortium, Bussemaker H.J., Morris, Q.D., Bulyk, M,L,Stolovitsky G., Hughes, T.R.; Evaluation of methods for modeling transcription factor sequence specificity; Nature Biotechnology 31, 126–134 (2013) doi:10.1038/nbt.2486

Prill, R.J. and Saez-rodriguez, J. and Alexopoulos, L.G. and Sorger, P.K. and Stolovitzky, G.; Crowdsourcing network inference: the DREAM predictive signaling network challenge; Sci Signal. 2011 Aug 30;4(189):mr7. doi:10.1126/scisignal.2002212

Marbach, D. and Costello, J.C. and Kueffner R. and Vega, N.D. and Prill, R.J. and Camacho, D.M. and Allison, K.R. and the DREAM5 Consortium and Kellis, M. and Collins J.J. and Stolovitzky, G.; Wisdom of crowds for robust gene network inference; Nature Methods 9, 796–804 (2012) doi:10.1038/nmeth.2016

Prill, R.J. and Marbach, D. Saez-rodriguez, J. and Sorger, P.K. and Alexopoulos, L.G. and Xue, X. and Clarke, N.D. and Altan-bonnet, G. and Stolovitzky, G.; Towards a rigorous assessment of systems biology models: the DREAM3 challenges; PLoS ONE 5(2): e9202. doi:10.1371/journal.pone.0009202

Marbach D, Prill RJ, Schaffter T, Mattiussi C, Floreano D, Stolovitzky G.; Revealing strengths and weaknesses of methods for gene network inference.; Proc Natl Acad Sci U S A. 2010 Apr 6;107(14):6286-91. doi: 10.1073/pnas.0913357107. Epub 2010 Mar 22.

Stolovitzky, G. and Kahlem, P. and Califano, A.; Annals of the New York Academy of Sciences Volume 1158: The Challenges of Systems Biology Community Efforts to Harness Biological Complexity: Preface, Annals of the New York Academy of Sciences, 1158: ix–xii. doi:10.1111/j.1749-6632.2009.04470.x

Stolovitzky, G and Prill, R. J and Califano, A.; Lessons from the DREAM2 Challenges; Annals of the New York Academy of Sciences, 1158: 159–195. doi:10.1111/j.1749-6632.2009.04497.x

Stolovitzky, G. and Monroe, D. and Califano, A.; Dialogue on Reverse-Engineering Assessment and Methods; Annals of the New York Academy of Sciences, 1115: 1–22. doi:10.1196/annals.1407.021; Stolovitzky, G. and Califano, A.; Preface Annals of the New York Academy of Sciences, 1115: xi–xiv. doi:10.1196/annals.1407.022