Dates: 19-20 April, 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.
(include but not limited to)
- Single Cell Systems Biology
- Cancer epidemiology
- Crowdsourced science
- Data sharing
Tuesday April 19th
DREAM challenges and EPIDEMIUM@RECOMB I
Tuesday April 20th
DREAM challenges and EPIDEMIUM@RECOMB II
ETH Zürich, Switzerland
Mines ParisTech, France
Mines ParisTech, France
Keynote/discussion: Open science with community : pitfalls of organizing collaborative scientific process
- Context : pitfalls of open science
- Lessons learned from collaborative open science program Epidemium
- Iterative scientific process
- Mechanisms and tools to support successful open science campaign
Workshop 1: Designing your collaborative open science campaign
A growing amount of scientific research is done in
an open manner. Numerous examples demonstrate that open initiatives
including crowd, citizen- or open science are dealing with more and
more complex problems, moving towards producing more tangible
results. Still, open science approach is not widely used practice by
researchers. Then why is it difficult to create tangible scientific
outputs with crowds? What are the pain points that actors face today
and how to avoid them? How to ensure the success of your open science
initiatives? What is the future of collaborative open science? We
invite you to our collaborative session that brings together
practitioners & researchers. Our goal is to discuss open science
challenges that actors face and to identify together how they can be
- Interactive session : 1. Spot current limits of open science challenges, 2.
Design your open science campaign : participants and organizers’
- Wrap up: On the future of open science and
collective intelligence approaches
Workshop 2: RAMP challenge (BRING YOUR LAPTOPS!)
To be confirmed if enough participants (Sign-up now)
Monoclonal antibodies constitute one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. In order to guarantee the quality of those preparations prepared at hospital, quality control has to be developed. The aim of this study was to explore a noninvasive, nondestructive, and rapid analytical method to ensure the quality of the final preparation without causing any delay in the process. We analyzed four mAbs (Inlfiximab, Bevacizumab, Ramucirumab and Rituximab) diluted at therapeutic con- centration in chloride sodium 0.9% using Raman spectroscopy. To reduce the prediction errors obtained with traditional chemometric data analysis, we will ask participants to the RAMP challenge to use a data-driven approach to:
A total of 360 Raman spectra were collected for each of the four mAbs agents at 10 different concentrations and 12 different trials, except for Ramucirumab (348 spectra), from these 1428 measurements, 429 test instances were randomly selected to be used as test set, the 999 spectra left as training set.
The results will be evaluated first through a classification error of the drug and its corresponding Raman spectra and then a mean absolute relative error (MARE) on the prediction of the drug concentration based on the Raman spectra. The overall score will be a balance of 2/3 classification score and 1/3 regression score (see Fig.1).
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.
A baseline model is available here.
- Olivier de Fresnoye (Epidemium)
- Julio Saez-Rodriguez (RWTH Aachen University)
- Pablo Meyer-Rojas (IBM)
- Gustavo Stolovitzky (IBM)
- Elise Blaese (IBM)