Speaker: DonKulasiri, Professor of Computational Modelling and Systems Biology, Lincoln University, New Zealand

Time: 15:00-16:00 p.m., November 9, 2023, GMT+8

Venue: Lui Che-woo Building B101

Abstract:

We present brief summaries of two computational biology problems we have been working on. The first one deals with numerical solutions of the chemical master equation (CME) to understand the stochasticity of biochemical systems. Solving CMEs is a formidable task. This task is complicated due to the nonlinear nature of the reactions and the size of the networks which result in different realizations. Most importantly, the exponential growth of the size of the state-space, with respect to the number of different species in the system makes this a challenging assignment. When the biochemical system has a large number of variables, the CME solution becomes intractable. We introduce the intelligent state projection (ISP) method to use in the stochastic analysis of these systems. ISP is based on a state-space search and the data structure standards of artificial intelligence (AI). It can be used to explore and update the states of a biochemical system. To support the expansion in ISP, we also develop a Bayesian likelihood node projection (BLNP) function to predict the likelihood of the states. To demonstrate the acceptability and effectiveness of our method, we apply the ISP method to several biological models discussed in prior literature. The results of our computational experiments reveal that the ISP method is effective both in terms of the speed and accuracy of the expansion, and the accuracy of the solution.

Source: PKU School of Pharmaceutical Sciences