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Approximating Solutions of the Chemical Master Equation using Neural Networks

June 3, 2022 @ 1:00 pm - 2:00 pm KST

B378 Seminar room, IBS, 55 Expo-ro Yuseong-gu
Daejeon, 34126 Korea, Republic of

Speaker

Hyeontae Jo
Biomedical Mathematics Group, IBS

We will discuss about “Approximating Solutions of the Chemical Master Equation using Neural Networks”, Sukys et al., bioRxiv, 2022

Abstract: The Chemical Master Equation (CME) provides an accurate description of stochastic biochemical reaction networks in well-mixed conditions, but it cannot be solved analytically for most systems of practical interest. While Monte Carlo methods provide a principled means to probe the system dy- namics, their high computational cost can render the estimation of molecule number distributions and other numerical tasks infeasible due to the large number of repeated simulations typically required. In this paper we aim to leverage the representational power of neural networks to approximate the solutions of the CME and propose a framework for Neural Estimation of Stochastic Simulations for Inference and Exploration (Nessie). Our approach is based on training a neural network to learn the distributions predicted by the CME from a relatively small number of stochastic simulations, thereby accelerating computationally intensive tasks such as parameter exploration and inference. We show on biologically relevant examples that simple neural networks with one hidden layer are able to cap- ture highly complex distributions across parameter space. We provide a detailed discussion of the neural network implementation and code for easy reproducibility.

Details

Date:
June 3, 2022
Time:
1:00 pm - 2:00 pm KST
Event Category:

Venue

B378 Seminar room, IBS
55 Expo-ro Yuseong-gu
Daejeon, 34126 Korea, Republic of

Organizer

Jae Kyoung Kim
Email
jaekkim@kaist.ac.kr
IBS 의생명수학그룹 Biomedical Mathematics Group
기초과학연구원 수리및계산과학연구단 의생명수학그룹
대전 유성구 엑스포로 55 (우) 34126
IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
55 Expo-ro Yuseong-gu Daejeon 34126 South Korea
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