Journal Club

We will discuss about “MultiVI: deep generative model for the integration of multimodal data” Nature Methods 20.8 (2023): 1222-1231. Abstract Jointly profiling the transcriptome, chromatin accessibility and other molecular properties of single cells offers a powerful way to study cellular diversity. Here we present MultiVI, a probabilistic model to analyze such multiomic data and leverage …

We will discuss about “Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery” IEEE Transactions on neural networks and learning systems 32.9 (2020): 4166-4177. Abstract Symbolic regression is a powerful technique to discover analytic equations that describe data, which can lead to explainable models and the ability to predict unseen data. In …

We will discuss about "AI Feynman: A physics-inspired method for symbolic regression",Science Advances 6.16 (2020): eaay2631. Abstract A core challenge for both physics and artificial intelligence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle, functions of practical interest …

We will discuss about "The timing of cellular events: a stochastic vs deterministic perspective", bioRxiv (2023): 2023-07.   Abstract Changes in cell state are driven by key molecular events whose timing can often be measured experimentally. Of particular interest is the time taken for the levels of RNA or protein molecules to reach a critical threshold …

We will discuss about "Linear mapping approximation of gene regulatory networks with stochastic dynamics", Nature communications 9.1 (2018): 3305.   Abstract The presence of protein–DNA binding reactions often leads to analytically intractable models of stochastic gene expression. Here we present the linear-mapping approximation that maps systems with protein–promoter interactions onto approximately equivalent systems with no binding …

We will discuss about “A trade-off in controlling upstream and downstream noise in signaling networks”, bioRxiv (2023): 2023-08.   Abstract Signal transduction, underpinning the function of a variety of biological systems, is inevitably affected by fluctuations. It remains intriguing how the timescale of a signaling network relates to its capability of noise control, specifically, whether long …

We will discuss about “Anticipating the occurrence and type of critical transitions”, Science Advances 9.1 (2023): eabq4558.   Abstract Critical transition can occur in many real-world systems. The ability to forecast the occurrence of transition is of major interest in a range of contexts. Various early warning signals (EWSs) have been developed to anticipate the …

We will discuss about “A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples ”, Nature communications 14.1 (2023): 7286.   Abstract Pseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many methods have been developed to infer the pseudotemporal trajectories …

We will discuss about "Reduced model for female endocrine dynamics: Validation and functional variations." Mathematical Biosciences 358 (2023): 108979. Abstract A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle …

We will discuss about “Transcriptome-wide analysis of cell cycle-dependent bursty gene expression from single-cell RNA-seq data using mechanistic model-based inference”, bioRxiv (2024) Abstract Bursty gene expression is quantified by two intuitive parameters: the burst frequency and the burst size. While these parameters are known to be cell-cycle dependent for some genes, a transcriptome-wide picture remains …

We will discuss about "Anti-Windup Protection Circuits for Biomolecular Integral Controllers", bioRxiv (2023).   Abstract Robust Perfect Adaptation (RPA) is a desired property of biological systems wherein a system’s output perfectly adapts to a steady state, irrespective of a broad class of perturbations. Achieving RPA typically requires the deployment of integral controllers, which continually adjust …

We will discuss about "Phenotypic switching in gene regulatory networks", PNAS (2014).   Abstract Noise in gene expression can lead to reversible phenotypic switching. Several experimental studies have shown that the abundance distributions of proteins in a population of isogenic cells may display multiple distinct maxima. Each of these maxima may be associated with a …