Workshop on Stochasticity in Biochemical Reaction Networks (13w2162)

Arriving in Banff, Alberta Friday, September 13 and departing Sunday September 15, 2013

Organizers

(Harvard University)

(University of Vermont)

(University of California, Berkeley)

(FOM Institute AMOLF)

Objectives

An increased understanding of the stochasticity in individual cells has revolutionized the way scientists think about key biological processes including evolution, development, and disease. Mathematical tools for modeling and analyzing stochasticity play a critical role in understanding the origins and implications of this biological variability. New mathematical and statistical techniques, including methods that allow for efficient modeling of rare events and spatial heterogeneity, will improve understanding of complex cellular dynamics. This workshop acts as a bridge between scientists from mathematics, statistics, engineering, and the physical sciences, providing an environment to exchange ideas, develop collaborations, and inspire new theoretical and experimental approaches.

Objectives: The workshop is organized around two objectives: First, to provide an overview of the state-of-the-art in mathematical, statistical, and experimental methods for studying stochastic biochemical systems. Second, to provide a forum for discussing the new tools that are needed to advance the field. We will ask participants from diverse backgrounds, including theoreticians, scientists, and engineers to provide updates on recent innovations in complementary research areas, such as the latest computational and theoretical tools and newly developed experimental approaches. From this foundation we hope to promote an intense and creative conversation that will generate questions to drive the field forward by involving both new and established voices. To be an effective workshop, a synergy must arise not simply from presentation of techniques but through earnest discussion of current limitations and potential. A more detailed representation of these objectives follows below.

What new mathematical and computational tools can help us efficiently infer biological mechanisms from statistical data?
The workshop will discuss new mathematical and computational tools to efficiently simulate rare events, which are necessary for testing models of stochastic biochemical processes that occur over long time scales (such as evolution). In addition, we hope to foster discussion on new methods to efficiently distinguish best fit models for large data sets, and approaches to prevent over-fitting with unnecessarily complex models.

What is the role of spatial organization in stochastic regulation? How can mathematical modeling contribute to understanding of spatial stochastic effects?
Many crucial biological processes, such as cell division, embryonic development, and gene regulation require spatial precision at the length scale of a single cell down to a single molecule. How does cellular machinery achieve such tight precision given the stochastic nature of its components? Conversely, can the active processes that induce spatial heterogeneity, such as compartmentalization or localization to the membrane, actually act to reduce the stochasticity in biochemical signaling? Recent mathematical advances in modeling spatial stochasticity can provide answers to these questions from a theoretical perspective.

Can stochastic biochemical processes be designed and constructed guided by predictions from mathematical models?
Cells can exploit stochastic variation in populations, but is it possible to engineer systems that use noise to their advantage? For example, can populations be subdivided to allow for multitasking? As our computational and theoretical understanding of cell regulation improves, it may be possible to design novel stochastic circuits that can be used to drive processes in the cell. These results will be of great interest to the field of synthetic biology, introducing new devices for controlling cellular regulation, and mathematical models of these systems can guide design.

Feedback from previous workshops demonstrates importance to field and researchers

Feedback from last year's workshop highlights the unique supportive role that this meeting has for the participants and the field of stochastic mathematical biology. No other conference or workshop achieves the cross-disciplinary fertilization of ideas that has been achieved at past BIRS workshops. In the anonymous workshop evaluations from 2011, the quality of talks, choice of participants, scientific organization, and choice of location all scored between Excellent and Exceptional on a numeric feedback scale.

Many researchers indicated the start of new collaborations:

``I was able to establish collaborations with two different scientists during this event, which would have been extremely hard to achieve without such an intimate environment."

``The amply allocated discussion time allowed for deep communication with people whom I'm unlikely to have interacted with otherwise, and has led to three (or possibly more) concrete leads for future collaborations. This would not have occurred in a typical conference setting."


The unique environment at BIRS was frequently cited as contributing to the success of the workshop:

`` BIRS is a very efficiently run center which provides very good facilities and otherwise gets out of the way. The location at the Banff center is ideal for generating discussions due to the special combination of quiet and a stimulating atmosphere around the campus."

``BIRS is THE place to have this kind of workshop.''

Many researchers indicated this workshop had a special impact on their research and the field in general:

``Very much like the emphasis on promoting the field in a collaborative way - this is exemplary!"

``I think this is one of the workshops that has made the greatest advance to my research.''

``I really enjoyed the feeling that we were on the cutting edge of defining the future course of this very new field of study."

``This was the BEST workshop I ever attended. I learned deeply from topic that I believed to be out of my specific field but turned out to be very close. I feel this will mark a before/after point in my career."