Accèder directement au contenu

David Holcman

Group of Applied Mathematics and Computational biology

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

Our main interest is to

  • Analyze, quantify and predict the function of nano- and micro- domains in cell biology and neurobiology from structures and biochemistry.
  • Identify principles and computational rules underlying cellular and network functions.
  • Develop predictive model and computational methods for medical applications (EEG for coma, anesthesia,etc...).
  • Construct mathematical frameworks (analysis, simulations and softwares).

Methods :
We develop physical modeling, mathematical analysis, numerical simulations, software and data analysis (Big data of super-resolution single particle trajectories, Hi-C analysis and EEG data basis).

Main focus on basic science and predictive medicine.

For the past 10 years, we focused on molecular trafficking, synaptic transmission in neurons and nuclear organization. Our aim is now to understand how the subcellular scale controls cellular responses in networks, such as neuron-glia networks in normal and pathological conditions.

Breaking news of the lab :

  • 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 .
  • Khanh Dao duc has become (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.
  • 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 :

M. Dora, D. Holcman, ER trafficking by packets, Philo. Trans. Royal Soc. B London, 2020 (to appear).

M. Heine, D. Holcman, Asymmetric transient pre- and post-synaptic nanodomains underlying neuronal communication, Trends in Neuroscience, 2020.

O Shukron, V Piras, D Noordermeer, D Holcman,Statistics of chromatin organization during cell differentiation revealed by heterogeneous cross-linked polymers, Nature Comm 2019.

K Basnayake, D. Mazau A. Bemelman, N. Rouach, E Korkotian, D Holcman,Fast calcium transients in neuronal spines driven by extreme statistics, PLOS Biology 2019.

Jennifer Heck, Pierre Parutto, Anna Ciuraszkiewicz, Arthur Bikbaev, Romy Freund, Anna Fejtova, David Holcman* Martin Heine*, Mobile Calcium Channels Contribute to Variability of Pre-synaptic Transmitter Release, Neuron 2019.

Z Schuss, K Basnayake, D Holcman, Redundancy principle and the role of extreme statistics in molecular and cellular biology, Physics of life reviews, 2019

D. Holcman*c, P. Parutto*, J Chambers, L Young, S. Marciniak, C. Kaminski, D. Ron, E. Avezov* c, Statistical analysis of super-resolution single particle trajectories reveals the functional topology of the Endoplasmic Reticulum controlling molecular flows, Nature Cell Biology, 2018.

Cartailler J, Kwon T, Yuste R, Holcman D., Deconvolution of Voltage Sensor Time Series and Electro-diffusion Modeling Reveal the Role of Spine Geometry in Controlling Synaptic Strength. Neuron. 2018 Mar 7 ;97(5).

Amitai A, Holcman D, Polymer physics of nuclear organization and function, Physics Report, 2017.

Amitai A, Seeber A, Gasser SM, Holcman D, Visualization of Chromatin Decompaction and Break Site Extrusion as Predicted by Statistical Polymer Modeling of Single-Locus Trajectories. Cell Rep. 2017 ;18(5):1200-1214.

D Holcman, N Hozé, Statistical Methods of Short Super-Resolution Stochastic Single Trajectories Analysis, Annual Review of Statistics and Its Application 4 (1) 2017.

Youtube presentation of the group :


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

1-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 develop polymer simulations and derived polymer looping formula using expansion of eigenvalues in high dimensional space.
  • 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.

2-Theory of diffusion in microdomains : we are currently developing a theory to describe the escape through small openings and the analysis of single stochastic trajectories. This approach allows modeling and predicting some information about the homologous repair process occurring in the nucleus.

3-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 built a complete model of the single photonresponse including dark noise in rods and cones.

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). This computation defines the forward binding rate of chemical reactions occurring in microdomains.


Fields : Computational Biology, Applied Mathematics, Modeling-Machine-Learning, Asymptotic analysis, Applied Probability, Partial Differential Equations, Brownian simulations, Mathematical Biology, Computational Neuroscience, Large data analysis, Physical Virology, Phototransduction, Polymer Modeling, Analysis of single particle trajectory, Neuron-glia interactions, Nuclear Organization, Statistical Biophysics, Predictive medecine, EEG analysis, Deconvolution method for electrophysiological time series, Coma Brain analysis.

Sub-Fields :
Diffusion, Data Geometry, Brownian Motion, Narrow Escape Time, Dire Strait Time, Asymptotic methods, Mean First Passage Time methods, Markov chains, Hybrid simulations, Statistical methods (extended Gaussian Mixture Model, Wavelet decomposition and comparison methods, 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. Superresolution data analysis, boundary layer methods, dsDNA break analysis, dendritic spines, modeling calcium dynamics, looping time, synaptic transmission.

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

PDF - 292.1 ko