Institut de Biologie de l'École Normale Supérieure ENS . CNRS UMR8197 . Inserm U1024 Directeur : Pierre Paoletti

Group of Data Modeling, Computational NeuroBiology and Predictive Medicine

Applied Mathematics. This page is a transfer of the previous WEB-PAGE-AT-ENS

Our main interest is to

• Identify and implement computational principles and rules underlying Brain function, at multiple scales : cellular and neuronal network functions.
• Develop mathematical models, algorithms and data analysis, classification methods for medical applications (time series analysis, EEG recorded during coma, anesthesia, etc...).
• Quantify and predict the function of nano- and micro- domains in cell biology and neurobiology based on local structures and biochemistry network.
• Methods :
  We develop data modeling, stochastic processes, mathematical computations, numerical simulations, algorithms and softwares to extract features from large datasets (Big data of super-resolution single particle trajectories, Hi-C analysis, calcium time series, and EEG data basis).

Basic science and predictive medicine.

We focus on molecular trafficking on membranes and in organelles such as the reticulum endoplasmic. We have studied and modeled synaptic transmission, and develop polymer models to study nuclear organization. We apply our methods to predict the brain during anesthesia and coma. Our aim is currently to understand how the subcellular scale controls cellular responses in neuronal networks, such as neuron-glia networks.

Breaking news of the lab :

• Our novel method to analyse single particle trajectory in Cell Reports Methods (October 2022) *Cover page
• French Newspaper "le Monde" (April 2022) popularize the concept of predictive anesthesia and the real-time algorithm to predict brain sensitivity developed by C. Sun in the lab.
• Cover page on exteme statistics with swtiching European J. of physics B
• Matteo Dora defended successfully his PhD in May 2022.
• Lou Zonca defended successfully her PhD in July 2021.
• Kaniska Basnayake defended successfully his PhD in Dec 2020.
• Assaf Amitai, former PhD of the lab has been appointed senior research in 2020 at Genetech, in San Francisco, USA.
• D. Holcman has received the "pre-maturation" CNRS award for his work on predicting anesthesia using modeling-machine-learning.
• D. Holcman has been laureate of the ERC-Advanced grant 2020.
• Trends in Neuroscience (TINS March 2020) has dedicated the cover to the potential well theory to described high-density regions of channels and receptor in neuronal cells

  

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• Khanh Dao duc became (2019) an Assistant Professor at UBC, Vancouver in the department of Applied Mathematics. We congratulate him again for his fantastic trajectory.
• Claire Guerrier has just been appointed assistant Professor (CNRS) at the U. of Nice 2018.
• Thibault Lagache, former PhD is now associate researcher at Columbia University, NY 2017. He has now been appointed in 2018 research at the Pasteur Institute
• We congratulate Juergen Reingruber for his HDR Dec 5 2016.
• Marzhieh and Jing got married last year : we wish them a lot of happiness. 2016.
• A. Biess (postdoc in 2007) became an Assistant Professor at Ben Gourion University.

Striking recent peer reviewed publications of the lab :

Youtube presentation of the group :

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How to join the lab ?

1. at the master level : enroll in our class that belongs to Master 2 of Paris VI (Applied mathematics) or interdisciplinary Master at ENS (Imalys)
2. at a PhD level : you must have spent 6 months of training period in the lab.
3. at a postdoc level : physicists, mathematicians, computer scientists are welcome to apply.
4. at a senior level : we are 3 senior researchers. Please contact D. Holcman

Some projects

– Modeling Covid and implication to predict hospital cases. We are developing novel modeling to predict hospitalized patients.

– Predicting Brain state from EEG during Anesthesia. We are developing methods to analyse EEG and predict the Brain states.

– Applied mathematics and probability, Mathematical Modeling and analysis.
* We are developing asymptotic methods and Brownian simulations, to compute mean first passage time formulas, with applications to chemical reactions in microdomains.

* We are developing methods to reconstruct neuronal connectivity from time series using explicit models and computation of the spectrum of the non-self adjoint Fokker- Planck operator. We use oscillation behavior of the escape time for a stochastic process to an unstable limit cycle to reconstruct the mean connectivity underlying Up/down state dynamics.

– Synaptic transmission, trafficking and voltage dynamics in dendrites : we are developing model of synaptic transmission and tools to extract features from superresolution data. We use the Poisson-Nernst-Planck equations to model the voltage dynamics at excitatory synapses and investigate the role of the local geometry.

Other projects in integrative biology concern sensor cells, such as photoreceptors, where we build model of the single photonresponse including dark noise in rods and cones (Juergen Reingruber).

In the past, by using asymptotic analysis, we computed the expansion of the mean time for a Brownian molecule to escape through a small hole located on a piece of a cell membrane (Narrow escape problem (See WIKI)). This computation defines the forward binding rate of chemical reactions occurring in microdomains.

Keywords

Fields : Computational Neuroscience, Mathematical Biology, Statistical Biophysics, Predictive medicine, Applied Mathematics, Model-Machine-Learning, Asymptotic analysis, Applied Probability, Large data analysis, Physical Virology, Photo-transduction, EEG analysis, Deconvolution method for electrophysiological time series, Coma Brain analysis, Polymer Modeling, Neuron-glia interactions, Nuclear Organization.

Sub-Fields :
Diffusion, Data Geometry, Partial Differential Equations, Brownian simulations,,Brownian Motion, Narrow Escape Time, Dire Strait Time, Asymptotic methods, Mean First Passage Times, Markov chains, Hybrid simulations, Statistical methods (extended Gaussian Mixture Model, Wavelet decomposition and comparison methods, Analysis of single particle trajectory, Stochatic simulations, Aggregation-Dissociation model, Conformal methods, WKB expansion, boundary layer analysis, polymer looping, modeling telomere organization, Molecular and Vesicular Trafficking, Synaptic Transmission, Numerical methods, Early Steps of Viral Infection, Neurite outgrowth. Super-resolution data analysis, boundary layer methods, dsDNA break, dendritic spines, modeling calcium dynamics, looping time, synaptic transmission.

More about our research :
More about our past research in french :

copyrights@David Holcman, free to use with appropriate reference.