Research graph
References from Reconstructing noisy gene regulation dynamics using extrinsic-noise-driven neural stochastic differential equations. Local targets link to admitted publications; unresolved targets remain external evidence.
Intrinsic and extrinsic contributions to stochasticity in gene expression
10.1073/pnas.162041399 · 2002 · External reference
Stochastic gene expression in a single cell
10.1126/science.1070919 · 2002 · External reference
Regulation of noise in gene expression
10.1146/annurev-biophys-083012-130401 · 2013 · External reference
Mammalian gene expression variability is explained by underlying cell state
10.15252/msb.20199146 · 2020 · External reference
Identifying Noise Sources governing cell-to-cell variability
10.1016/j.coisb.2017.11.013 · 2018 · External reference
Intrinsic noise in gene regulatory networks
10.1073/pnas.151588598 · 2001 · External reference
Noise in biology
10.1088/0034-4885/77/2/026601 · 2014 · External reference
Estimating intrinsic and extrinsic noise from single-cell gene expression measurements
10.1515/sagmb-2016-0002 · 2016 · External reference
What population reveals about individual cell identity: single-cell parameter estimation of models of gene expression in yeast
10.1371/journal.pcbi.1004706 · 2016 · External reference
A simple and flexible computational framework for inferring sources of heterogeneity from single-cell dynamics
2019 · External reference
Quantifying intrinsic and extrinsic noise in gene transcription using the linear noise approximation: an application to single cell data
2013 · External reference
Quantifying extrinsic noise in gene expression using the maximum entropy framework
10.1016/j.bpj.2013.05.010 · 2013 · External reference
Advanced methods for gene network identification and noise decomposition from single-cell data
10.1038/s41467-024-49177-1 · 2024 · External reference
Stochastic mRNA synthesis in mammalian cells
2006 · External reference
Control of stochasticity in eukaryotic gene expression
10.1126/science.1098641 · 2004 · External reference
Variability and memory of protein levels in human cells
10.1038/nature05316 · 2006 · External reference
Dynamics of protein noise can distinguish between alternate sources of gene-expression variability
10.1038/msb.2012.38 · 2012 · External reference
Models of stochastic gene expression
10.1016/j.plrev.2005.03.003 · 2005 · External reference
Quantifying intrinsic and extrinsic variability in stochastic gene expression models
10.1371/journal.pone.0084301 · 2013 · External reference
Roles of cellular heterogeneity, intrinsic and extrinsic noise in variability of p53 oscillation
10.1038/s41598-019-41904-9 · 2019 · External reference
150 years of the mass action law
2015 · External reference
Cato Guldberg and Peter Waage, the history of the Law of Mass Action, and its relevance to clinical pharmacology
10.1111/bcp.12721 · 2016 · External reference
Metastability in a stochastic neural network modeled as a velocity jump Markov process
10.1137/120898978 · 2013 · External reference
Unresolved reference
1976 · External reference
Stochastic delay differential equations for genetic regulatory networks
10.1016/j.cam.2006.02.063 · 2007 · External reference
A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae
10.1093/bioinformatics/bti415 · 2005 · External reference
Kinetic theories of state- and generation-dependent cell populations
10.1103/physreve.110.064146 · 2024 · External reference
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings
10.1038/nmeth.2794 · 2014 · External reference
Approximating solutions of the Chemical Master equation using neural networks
10.1016/j.isci.2022.105010 · 2022 · External reference
Inference and uncertainty quantification of stochastic gene expression via synthetic models
10.1098/rsif.2022.0153 · 2022 · External reference
Efficient and scalable prediction of stochastic reaction-diffusion processes using graph neural networks
10.1016/j.mbs.2024.109248 · 2024 · External reference
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An efficient Wasserstein-distance approach for reconstructing jump-diffusion processes using parameterized neural networks
2024 · External reference
A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
2024 · External reference
A new local time-decoupled squared Wasserstein-2 method for training stochastic neural networks to reconstruct uncertain parameters in dynamical systems
2025 · External reference
Learning dynamical systems from data: an introduction to physics-guided deep learning
2024 · External reference
Modeling circadian clocks: from equations to oscillations
10.2478/s11535-011-0061-5 · 2011 · External reference
Quantification of circadian rhythms in single cells
10.1371/journal.pcbi.1000580 · 2009 · External reference
Replication protein A: a multifunctional protein with roles in DNA replication, repair and beyond
10.1093/narcan/zcaa022 · 2020 · External reference
Dynamic elements of replication protein A at the crossroads of DNA replication, recombination, and repair
10.1080/10409238.2020.1813070 · 2020 · External reference
Functions of Replication Protein A as a Sensor of R Loops and a Regulator of RNaseH1
10.1016/j.molcel.2017.01.029 · 2017 · External reference
Replication protein A: a heterotrimeric, single-stranded DNA-binding protein required for eukaryotic DNA metabolism
10.1146/annurev.biochem.66.1.61 · 1997 · External reference
ssDNA accessibility of Rad51 is regulated by orchestrating multiple RPA dynamics
10.1038/s41467-023-39579-y · 2023 · External reference
Exact stochastic simulation of coupled chemical reactions
10.1021/j100540a008 · 1977 · External reference
The chemical Langevin equation
10.1063/1.481811 · 2000 · External reference
Stimulus-specificity in the responses of immune sentinel cells
10.1016/j.coisb.2019.10.011 · 2019 · External reference
Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses
10.1016/j.immuni.2021.04.011 · 2021 · External reference
The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation
10.1126/science.1071914 · 2002 · External reference
NF-κB dynamics determine the stimulus specificity of epigenomic reprogramming in macrophages
10.1126/science.abc0269 · 2021 · External reference
Gene regulatory strategies that decode the duration of NFκB dynamics contribute to LPS- versus TNF-specific gene expression
2020 · External reference
Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses
10.1016/j.immuni.2021.04.011 · 2021 · External reference
Modeling heterogeneous signaling dynamics of macrophages reveals principles of information transmission in stimulus responses.
10.1038/s41467-025-60901-3 · 2025 · External reference
10.1007/978-3-319-08488-6
10.1007/978-3-319-08488-6 · External reference
Noise effects in two different biological systems
10.1140/epjb/e2009-00162-y · 2009 · External reference
Biochemical fluctuations, optimisation and the linear noise approximation
10.1186/1752-0509-6-86 · 2012 · External reference
Intrinsic and extrinsic contributions to stochasticity in gene expression
10.1073/pnas.162041399 · 2002 · External reference
10.7551/mitpress/11171.001.0001
10.7551/mitpress/11171.001.0001 · External reference
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Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages
10.1038/s44320-024-00047-4 · 2024 · External reference
A shape-based similarity measure for time series data with ensemble learning
10.1007/s10044-011-0262-6 · 2013 · External reference
Learning force fields from stochastic trajectories
10.1103/physrevx.10.021009 · 2020 · External reference
Control, exploitation and tolerance of intracellular noise
10.1038/nature01258 · 2002 · External reference
Filtering transcriptional noise during development: concepts and mechanisms
10.1038/nrg1750 · 2006 · External reference
Challenges in measuring and understanding biological noise
10.1038/s41576-019-0130-6 · 2019 · External reference
A dimension reduction approach for energy landscape: identifying intermediate states in metabolism-EMT network
10.1002/advs.202003133 · 2021 · External reference
Landscape and kinetic path quantify critical transitions in epithelial-mesenchymal transition
10.1016/j.bpj.2021.08.043 · 2021 · External reference
Landscape and flux reveal a new global view and physical quantification of mammalian cell cycle
10.1073/pnas.1408628111 · 2014 · External reference
Near-optimal control of dynamical systems with neural ordinary differential equations
2022 · External reference
Visualizing high-dimensional loss landscapes with Hessian directions
10.1088/1742-5468/ad13fc · 2024 · External reference
Optimal control of agent-based models via surrogate modeling
10.1371/journal.pcbi.1012138 · 2025 · External reference
Control of medical digital twins with artificial neural networks
10.1098/rsta.2024.0228 · 2025 · External reference
Neural ordinary differential equation control of dynamics on graphs
10.1103/physrevresearch.4.013221 · 2022 · External reference
AI Pontryagin or how artificial neural networks learn to control dynamical systems
10.1038/s41467-021-27590-0 · 2022 · External reference
Interpretable polynomial neural ordinary differential equations
10.1063/5.0130803 · 2023 · External reference
NN2Poly: a polynomial representation for deep feed-forward artificial neural networks
10.1109/tnnls.2023.3330328 · 2025 · External reference
