We will discuss about “Data driven governing equations approximation using deep neural networks” Journal of Computational Physics (2019). Abstract We present a numerical framework for approximating unknown governing equations using observation data and deep neural networks (DNN). In particular, we propose to use residual network (ResNet) as the basic building block for equation approximation. We demonstrate that the ResNet block can be …

In this talk, we discuss the paper "Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe", by Xiaojie Qiu  et.al., Cell Syst. 2020. Abstract  Here, we present Scribe (https://github.com/aristoteleo/Scribe-py), a toolkit for detecting and visualizing causal regulatory interactions between genes and explore the potential for single-cell experiments to power network reconstruction. Scribe …

In this talk, we discuss the paper, "MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data" by Siyao Liu et.al.  Genome Biology, 2024. Abstract  Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) …

In this talk, we will discuss the paper, "A modified shuffled frog leaping algorithm with inertia weight", by Zhuanzhe Zhao et.al. , Scientific Reports, 2024. Abstract  The shuffled frog leaping algorithm (SFLA) is a promising metaheuristic bionics algorithm, which has been designed by the shuffled complex evolution and the particle swarm optimization (PSO) framework. However, …

In this talk, we discuss the paper "Holimap: an accurate and efficient method for solving stochastic gene network dynamics" by Chen Jia and Ramon Grima, bioRxiv, 2024. Abstract  Gene-gene interactions are crucial to the control of sub-cellular processes but our understanding of their stochastic dynamics is hindered by the lack of simulation methods that can accurately and efficiently …

In this talk, we discuss the paper "Stochastic representations of ion channel kinetics and exact stochastic simulation of neuronal dynamics" by D. F. Anderson, B. Ermentrout and P. J. Thomas, Journal of Computational Neuroscience, 2015. Abstract In this paper we provide two representations for stochastic ion channel kinetics, and compare the perfor- mance of exact …

In this talk, we discuss the paper "Temperature compensation through kinetic regulation in biochemical oscillators" by HaochenFu, Chenyi Fei, Qi Ouyang, and Yuhai Tu, to appear in PNAS.  Abstract  Although individual kinetic rates in biochemical reactions are sensitive to temperature, most circadian clocks exhibit a relatively constant period across a wide range of temperatures, a phenomenon called …

In this talk, we discuss the paper "RNA velocity of single sells" by Gioele La Manno et.al., Nature, 2018. Abstract RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput. However, this approach captures only a static snapshot at …