DREAM News

Author Archive | dreamadmin

January 17, 2018

Winners in the DREAM Parkinson’s Disease Digital Biomarker Challenge Announced

Sage Bionetworks in Collaboration with The Michael J. Fox Foundation Announce Winners in the DREAM Parkinson’s Disease Digital Biomarker Challenge. Sage Bionetworks announced today the results of the Parkinson’s Disease Digital Biomarker (PDDM) DREAM challenge, an open crowd-sourced research project designed to benchmark the use of remote sensors to diagnose and track Parkinson’s disease (PD). The winners of this Challenge developed methods that are 38% better than previous models at detecting Parkinson’s disease from a simple walk and balance test (read more)

November 13, 2017

New DREAM Video

Calling all DREAMers…  The DREAM team is developing a video project about DREAM and our community, and needs your help.  We need Selfies of you holding signs that say either  “DREAM Challenges”  or “DREAM” or “Wisdom of the Crowd” .  Take a sheet of white unlined copier paper and write as big as you can with a marker (so it is legible).  You can take one selfie with one message or three.   Then we will include them in the video of our community of DREAMers adding to the Wisdom of the Crowd.  (12/6/17 – Thanks for your help.. this is done.. Please see video on the DREAM home page or on Youtube – https://youtu.be/PrAA-DnTQ7w)

October 17, 2017

DREAM Challenges and EPIDEMIUM@RECOMB in Paris 2018

DREAM Challenges and EPIDEMIUM@RECOMB in Paris
 – April 19-20, 2018

The meeting will focus on proteogenomics, single cell systems biology and cancer epidemiology, and how crowdsourced science, data sharing and a culture of collaboration can help advance research in these fields. We will highlight the solutions of the top performing strategies in the Epidemium program in cancer epidemiology and the recent NCI-CPTAC Proteogenomics DREAM Challenge. We will also brainstorm as a community on the possibility of organizing a DREAM challenge on Single Cell Systems Biology.

 

December 6, 2016

DREAM 11- 2016 All-Stars

AstraZeneca-Sanger Drug Combination Prediction DREAM Challenge

Sub-Challenge 1A

Best Performer:
Team Guan Lab – Yuanfang Guan, University of Michigan (USA)

Tied 2nd Place:
Team: North Atlantic
az-northatlantic

Russ Wolfinger, SAS Institute Inc. (USA); Tin Nguyen & Sorin Draghici, Advaita Corporation and Wayne State University (USA); and Bence Szalai, Gábor Turu, Miklós Cserző, & László Hunyady: Semmelweis University, and MTA-SE Laboratory of Molecular Physiology (Hungary)

Team: Mikhail Zaslavskiy
Mikhail Zaslavskiy

Sub-challenge 1B

Best Performer:
Team Guan Lab – Yuanfang Guan, University of Michigan (USA)

Tied 2nd Place:
Team: DMIS
az-teamdimsjpg

Jaewoo Kang, Minji Jeon, Sunkyu Kim, Sungjoon Park, Heewon Lee, Hyeokyoon Chang, Minhwan Yu, and Kwanghun Choi, Korea University, (Korea)

Team: North Atlantic
Russ Wolfinger, SAS Institute Inc. (USA); Tin Nguyen & Sorin Draghici, Advaita Corporation and Wayne State University (USA); and Bence Szalai, Gábor Turu, Miklós Cserző, & László Hunyady: Semmelweis University, and MTA-SE Laboratory of Molecular Physiology (Hungary)

Team Puruguraming
Amin Allam, KAUST (Saudi Arabia)

Sub-challenge 2

Best Performer:
Team Guan Lab – Yuanfang Guan, University of Michigan (USA)

Team: North Atlantic
Russ Wolfinger, SAS Institute Inc. (USA); Tin Nguyen & Sorin Draghici, Advaita Corporation and Wayne State University (USA); and Bence Szalai, Gábor Turu, Miklós Cserző, & László Hunyady: Semmelweis University, and MTA-SE Laboratory of Molecular Physiology (Hungary)

 Disease Module Identification DREAM Challenge –

Sub-Challenge 1

Best Performer:
Team Tusk:
disease_module-tusk

Jake Crawford, Junyuan Lin, Xiaozhe Hu, Benjamin Hescott, Donna Slonim, & Lenore Cowen; Tufts University (USA)

Honorable Mentions:

Team Aleph:
disease_module-aleph
Sergio Gómez, Manlio De Domenico, Alex Arenas.

Team: Causality:
Weijia Zhang, Thuc Le, Taosheng Xu, Junpeng Zhang, Lin Liu, Jiuyong Li.

Team: PureMichigan:
Minjun Kim, Yuanfang Guan, University of Michigan (USA).

Team: ShanHeLab:
Dong Li, Benjapun Kaveelerdpotjana, Jiarui Zhou, Ning Shi, Weiqi Chen, Shan He.

Team: TeamDMIS:
Sungjoon Park, Wonho Shin, Minji Jeon, Sunwon Lee, Jaewoo Kang, Korea University, (Korea)

Team: Tianle Ma:
Tianle Ma.

Team: TripleAHC:
Hatem Hamza, Anton Heijs, Antonis Loizou, Andra Waagmeester, Christine Chichester.

Sub-Challenge 2

Team Tsurumi-Ono:
disease_module-tsunami
Artem Lysenko, Piotr J. Kamola, Keith A. Boroevich, & Tatsuhiko Tsunoda; RIKEN Center for Integrative Medical Sciences (Japan)

ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge

Conference Round

Team: autosome.ru
encode_autosome
Vsevolod Makeev, Andrey Lando, Grigory Sapunov, Ilya Vorontsov, Ivan Kulakovskiy, Valentina Boeva, & Irina Eliseeva; Russian Academy of Sciences; Moscow Institute of Physics and Technology; and Intento, (Russia) and Institut Cochin (France)

Team: J-Team
encode-j-team
Jens Keilwagen, Stefan Posch, & Jan Grau; Federal Research Centre for Cultivated Plants; and Martin Luther University Halle-Wittenberg  (Germany)

Team HINT
encode-hintjpg
Eduardo G. Gusmao, Zhijian Li, and  Ivan G. Costa; Aachen University Medical School  and RWTH Aachen University(Germany) Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health (USA)

ICGC-TCGA-DREAM Somatic Mutation Calling Challenge- Tumor Heterogeneity and Evolution (SMC-HET)

Team: GISL
smchet_gisl
Kaiyi Zhu, Tai-Hsien Ou Yang and Dimitris Anastassiou; Columbia University (USA)

Team: GuanLab
smchet_guan-lab-pg
Hongjiu Zhang and Yuanfang Guan; University of Michigan, (USA)

July 4, 2015

Daniel Marbach

Daniel MarbachIn the first edition of the DREAM challenges in 2007, I was a participant and best performer. Subsequently, I designed and led three editions of the DREAM network inference challenge (2008, 2009, 2010). Currently, I’m co-leading the DREAM gene essentiality prediction challenge. My involvement with DREAM has been a central part of my PhD thesis and postdoctoral work. I will continue my engagement with DREAM in the future to help promote open and collaborative science through crowdsourced challenges. Through my involvement with DREAM I changed my research focus from trying to show that my own methods work best, towards unbiased method assessment and creation of useful resources for the community. This work led to several highly cited papers that helped advance my academic career.

November 6, 2014

2014 Publications

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 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

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

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

October 22, 2014

Kevin Yip

When I participated in the DREAM3 in silico network reconstruction challenge, I had very little experience in reconstructing TF-regulatory networks (I was focusing on protein-protein interaction networks at that time). Given the many sophisticated methods existing at that time, I just hoped to participate and get some experience in this topic. However, perhaps because I was new to this topic, my method was apparently quite different from the other methods, and it seemed to put more emphasis on a new type of features (expression change due to perturbation) than the other methods, which turned out to be very useful. It has helped me to always ask if there are better features to use or better ways to use the existing features before drilling deep into improving subtle details of existing methods. I think this experience has guided my way to dealing with new problems.