CBBS-MS18

# Stochastic methods for biochemical reaction networks

#### Thursday, June 17 at 04:15am (PDT)

Thursday, June 17 at 12:15pm (BST)

Thursday, June 17 08:15pm (KST)

**MS19-CBBS**(click here).

**Organizers:**

#### Wasiur KhudaBukhsh (The Ohio State University, United States), Hye-Won Kang (University of Maryland at Baltimore County, United States)

**Description**:

Stochastic modelling is becoming increasingly popular in biological sciences. The ability to account for intrinsic fluctuations and uncertainty in experimental outcomes has been a crucial advantage of stochastic methods. The application of stochastic tools has proven to be useful in analysing biological data. In particular, stochastic methods have found usefulness in studying the spread of infectious diseases, in understanding the biophysics of enzyme kinetics, metabolism, immune-response mechanisms, and in constructing phylogenetic trees etc. The objective of this two-part mini-symposium is to highlight some of the recent advances in the field of stochastic biochemical reaction networks. Both sessions will cover a wide range of themes (including applications and techniques) giving a broad overview of the field. Specific topics include new asymptotic results/approximations, multi-scale methods, statistical inference algorithms and parameter identifiability issues. Special focus will be on methods that can be translated into usable tools from a practical perspective.

#### Ankit Gupta

*(ETH Zurich, Switzerland)*

###### "A deep learning approach for solving chemical master equations"

#### Grzegorz Rempala

*(The Ohio State University, United States)*

###### "Approximating bio-chemical dynamics using survival models"

#### Jinsu Kim

*(University of California Irvine, USA)*

###### "Mixing times for stochastically modeled biochemical reaction systems"

#### Wasiur KhudaBukhsh

*(The Ohio State University, United States)*