Challenges and Synergies in the Analysis of Large-Scale Population-Based Biomedical Data (17w5134)

Arriving in Oaxaca, Mexico Sunday, November 26 and departing Friday December 1, 2017

Organizers

(Microsoft Research)

(University of Toronto)

Objectives

While many fields can benefit from a cross-fertilization of ideas about how to model population-based data, we have selected these subfields to maximize the impact of our workshop: these prominent subfield have a shared mathematical language, have a substantial amount of available data, and are those that are likely to have the most immediate impact on human health.



Specific objectives include:



- Unify disparate fields that are separately developing ways to reconstruct and model populations of cells/organisms from genomic data thereby defining a new field of population genomics. - Share insights in dealing with issues of robustness to model misspecification (including noise models), multiple hypothesis testing, computational time and space complexity for classes of models (e.g. linear mixed models). -Elucidate and understand the common mathematical and computational modelling themes which are important to each of the defined areas, and how they relate to each other. -Leverage insights from one sub-field to another in a way that wouldn’t happen without such a meeting, which explicitly encourages the meeting of minds from these particular communities. (Note most of these people have never met, and are extremely excited by this meeting and ability to bridge areas, judging from their response to our email asking for support.) - Provide a forum for young investigators to meet and interact with leaders of their respective fields. -Discuss upcoming shared mathematical and computational challenges. -Generate new collaborations and lasting working relationships.