Journal Club

We will discuss about “Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming”, Cell (2019).   Abstract Understanding the molecular programs that guide differentiation during development is a major challenge. Here, we introduce Waddington-OT, an approach for studying developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. …

We will discuss about “PenDA, a rank-based method for personalized differential analysis: Application to lung cancer” Plos Computational Biology (2020). Abstract The hopes of precision medicine rely on our capacity to measure various high-throughput genomic information of a patient and to integrate them for personalized diagnosis and adapted treatment. Reaching these ambitious objectives will require …

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 …

In this talk, we discuss the paper "A universal description of stochastic oscillators", by Alberto Perez-Cervera et. al., PNAS, 2023. Abstract  Many systems in physics, chemistry, and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for example, linear dynamics of a stable focus with fluctuations, limit-cycle systems …

In this talk, we discuss the paper, "SMSSVD : Submatrix selection singular value decomposition", by Rasmus Henningsson and Magnus Fontes, Bioinformatics, 2019. Abstract Motivation High throughput biomedical measurements normally capture multiple overlaid biologically relevant signals and often also signals representing different types of technical artefacts like e.g. batch effects. Signal identification and decomposition are accordingly …