David Holcman is an applied mathematician, biophysicist and computational biologist at École Normale Supérieure in Paris. He is known for his work on the narrow escape problem, based on analysis of the Laplace equation, [1] [2] the redundancy principle in biology based on extreme statistics, [3] [4] [5] the modeling of molecular trafficking in neurobiology, of diffusion and electrodiffusion in nanodomains such as dendritic spines, the modeling of neuronal networks dynamics such as Up and Down states in electrophysiology. He developed multiscale methods and simulations to analyse large amount of molecular super-resolution trajectories, and polymer physics modeling and analysis to study cell nucleus organization. [6] These computational approaches led to several verified predictions in the life sciences such as nanocolumn organization of synapses [7] [8] or astrocytic protrusion penetrating neuronal synapses, [9] molecular ER organization in dendritic spines and many more. The narrow escape theory was recently verified in physical experiments. [10]
His research interests include mathematical biology, stochastic processes, data modeling, computational methods, stochastic simulations, theory of cellular microworld, neuronal networks, computational biology and neuroscience, asymptotic approaches in partial differential equations, predictive medicine, electroencephalography (EEG) analysis, and modeling organelles in cells. [11] Other contributions concern methods of analyzing single particle trajectories, calcium dynamics in dendritic spines and the development of statistical methods, polymer models, analysis and simulations to study chromatin and nucleus organization. [11] His recent works concern predicting the brain state transition during general anesthesia based on real-time operative multi-dimensional dynamics including time-frequency patterns and signal suppressions.
Holcman has more than 220 published journal articles and has registered 2 patents.
He is the co-author of the books:
Holcman has received several awards, including a Sloan-Keck fellowship award (2002) a Marie-Curie Award [12] (2013), and a Simons Fellowship. He is also recipient of 2 ERCs: an ERC Starting Grant [13] in mathematics (2007) and an ERC-Advanced Grant in computational biology [14] (2019).
David Holcman is an applied mathematician, biophysicist and computational biologist at École Normale Supérieure in Paris. He is known for his work on the narrow escape problem, based on analysis of the Laplace equation, [1] [2] the redundancy principle in biology based on extreme statistics, [3] [4] [5] the modeling of molecular trafficking in neurobiology, of diffusion and electrodiffusion in nanodomains such as dendritic spines, the modeling of neuronal networks dynamics such as Up and Down states in electrophysiology. He developed multiscale methods and simulations to analyse large amount of molecular super-resolution trajectories, and polymer physics modeling and analysis to study cell nucleus organization. [6] These computational approaches led to several verified predictions in the life sciences such as nanocolumn organization of synapses [7] [8] or astrocytic protrusion penetrating neuronal synapses, [9] molecular ER organization in dendritic spines and many more. The narrow escape theory was recently verified in physical experiments. [10]
His research interests include mathematical biology, stochastic processes, data modeling, computational methods, stochastic simulations, theory of cellular microworld, neuronal networks, computational biology and neuroscience, asymptotic approaches in partial differential equations, predictive medicine, electroencephalography (EEG) analysis, and modeling organelles in cells. [11] Other contributions concern methods of analyzing single particle trajectories, calcium dynamics in dendritic spines and the development of statistical methods, polymer models, analysis and simulations to study chromatin and nucleus organization. [11] His recent works concern predicting the brain state transition during general anesthesia based on real-time operative multi-dimensional dynamics including time-frequency patterns and signal suppressions.
Holcman has more than 220 published journal articles and has registered 2 patents.
He is the co-author of the books:
Holcman has received several awards, including a Sloan-Keck fellowship award (2002) a Marie-Curie Award [12] (2013), and a Simons Fellowship. He is also recipient of 2 ERCs: an ERC Starting Grant [13] in mathematics (2007) and an ERC-Advanced Grant in computational biology [14] (2019).