DREAM News
October 2, 2014

NEWS

February 26, 2019

PrecisionFDA and NCI CPTAC Announce the Best Performers in Multi-omics Sample Mislabeling Big Data Challenge

PrecisionFDA and the National Cancer Institute’s (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) (in coordination with DREAM Challenges) are pleased to announce the Best Performers in the first-ever Crowdsourced Multi-omics Sample Mislabeling Big Data Challenge. This unique challenge utilized proteogenomic datasets generated by CPTAC and clinical annotation information. A total of 230 submissions from participants around the globe were received and evaluated. Subchallenge 1 focused on the development of next-gen computational models for detecting mislabeled samples using proteomic and clinical data generated by CPTAC, while Subchallenge 2 took a step further, aiming to identify and correct mismatched samples with one data type mislabeled among three data types (clinical, transcriptomic, and proteomic data). Visit us to learn more about this big data computational multi-omics challenge and its best performers and come here them their findings at  DREAM Challenges@RECOMB 2019. (learn more)

January 31, 2019

Announcing Agenda for DREAM Challenges@RECOMB 2019

Join us at this years DREAM Challenges@RECOMB workshop on May 4, 2019 in Washington, DC at George Washington University.  This years’ workshop has two main objectives. The first objective is to present the final results of two recent Challenges: the FDA/NCI-CPTAC Multi-omics Enabled Sample Mislabeling Correction Challenge and the ICGC-TCGA DREAM Somatic Mutation Calling – RNA Fusion Detection Challenge. The second objective is to foster an in-depth dialogue between various big-data initiatives being carried out by different agencies in the US Federal Government (such as NCI and NASA) and the scientific community, to explore the role that crowd-sourced Challenges can play in increasing the creative use of data in big-data projects. For this we have invited administrators and scientists leading big data projects to present talks focusing on what these initiatives are doing programmatically and scientifically. This will be followed by a panel discussing how each of these initiatives could benefit by crowd-sourcing their data through scientific challenges. After the panel we will break into groups and work on potential challenges of relevance to these programs. The day should provide an incentive for large-scale data initiatives to leverage crowdsourced challenges as a strategy for enhanced data use by the community and an overview on the process of challenge organization from inception to results. (Learn more)

July 30, 2018

Call for Papers for DREAM Conference in December 2018!

This year we are inviting posters and oral presentations about past DREAM Challenges. We encourage participants to submit abstracts about their published or unpublished work on DREAM Challenges, such as the SMC Challenges, ENCODE challenge, the AZ synergy Challenge, etc. Abstracts may be either original unpublished work related to challenges or work that was published or accepted for publication in a journal previously. (Submit here)

March 19, 2018

Register NOW for DREAM Challenges and EPIDEMIUM@RECOMB in Paris 2018

Registration is open for DREAM Challenges and EPIDEMIUM@RECOMB April 19-20.   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, and have a RAMP Challenge Hands on Session.  The RAMP challenge will be divided into an initial individual phase followed by a collaborative phase of discussion. Solutions will be shown instantly in a leaderboard. Ensemble predictions will also be performed during the RAMP workshop.  Pre-Sign up for RAMP Session.  (30 participants needed to preregister to reserve the session.)  (Learn more)

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)

July 24, 2017

DREAM Challenge Community competition launches to learn how to use smartphone and wearable sensors to monitor health

Recent advances in mobile health have demonstrated great potential to leverage sensor-based technologies for remote monitoring of health and disease – particularly for diseases affecting motor function such as Parkinson’s. While there are many projects that have successfully collected sensor data from people in the real-world setting, researchers still have a poor understanding of what the data can tell us about health. (Read more.)

June 2, 2017

IBM and Sage Bionetworks announce winners of first phase of DREAM Digital Mammography Challenge

IBM and Sage Bionetworks announced today the winners of the first phase of its DREAM Digital Mammography (DM) Challenge have developed algorithms that had 5% fewer false-positive errors in breast cancer screenings than recently published state of the art computerized methods1. This 5 percent improvement could potentially lead to less anxiety and unnecessary procedures for an estimated two million women per year in the United States and could help reduce costs associated with follow-up exams and biopsies. (Read more)

June 2, 2017

Can Machine Learning Help Improve Accuracy in Breast Cancer Screening?

Breast Cancer is the most common cancer in women. It is estimated that one out of eight women will be diagnosed with breast cancer in their lifetime. The good news is that 99 percent of women whose breast cancer was detected early (stage 1 or 0) survive beyond five years after diagnosis, leading countries around the world to implement breast cancer screening programs for early detection. (Read more)