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Biophysical Modeling

We model and simulate the complex systems that arise in biology and soft condensed matter physics.

About

Our group aims to advance the understanding of fundamental biological phenomena.

To accomplish this, we formulate mechanistic models that bridge the gap between microscopic properties of key constituents and their macroscopic self-organization. We then analyze the mathematical structure of these models and develop new methods for their large-scale simulation while interacting very closely with experiment.

Areas of Focus

Dynamics Inside Nucleus

Dynamics Inside Cells

Multicellular Biophysics

Chiral Active Matter

Our Approach

By studying how specific biological systems function and developing appropriate methods, we often gain insights into broader biological and physical principles.

1. Observation

We begin by gathering high-quality data through experiments, performed either in-house or by our collaborators. This step is critical for identifying patterns, proposing hypotheses, and pinpointing the key constituents driving the biological phenomenon.

Fluorescent microscopic image of an oval-shaped cell containing two glowing blue circular structures.
A schematic illustration of a cell undergoing mitosis, showing a central spindle, two centrosomes with radiating microtubules, and surrounding elliptical membrane boundaries.

2. Large-Scale Simulation

Using state-of-the-art computational tools and high-performance computing resources, we translate our observations into detailed simulations. These allow us to explore complex, multi-scale phenomena with biologically-relevant particle numbers.

3. Reduced Order Modeling

Insights from microscopic simulations are distilled into coarse-grained models that encapsulate the core mechanisms of the systems under investigation. These models strike a balance between complexity and interpretability, enabling robust predictions and theoretical advancements.

A diagram of a cell showing microtubule growth with labels for nucleation, growth, catastrophe, stoichiometry, detachment, force, rotational drag, and elongation viscosity.
Scientific plots showing the movement of anterior and posterior cell structures over time, with a central diagram illustrating the experimental setup of two connected circular bodies with internal fibers.

4. Analysis

We rigorously analyze both simulations and models to uncover new insights, identify critical parameters, and validate results against experiments. The latter often involves advanced statistical methods, machine learning techniques, and collaboration with domain experts.

Latest News

  • Our paper about the physical consequences of sperm gigantism was published in Nature Physics and featured in the New York Times.

  • Our paper about dynamical arrest in defect-free active nematics and the consequences of defect proliferation was published in Phys. Rev. Research.

  • Our paper about the mechanics of the bacterial flagellar motor and its ultrasensitive response to external cues was published in Nature Physics.

A stylized illustration showing a broken, multicolored strand being repaired inside a blue, bean-shaped structure, representing DNA repair within a cell.

Physics-Informed AI Method Could Help Make CRISPR Safer

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Researchers Crack Mystery of Swirling Vortexes in Egg Cells

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Moving in Harmony

Publications

A stabilized finite element formulation for simulating ordered arrays of immersed flexible fibers with applications in cellular mechanics

Computer Methods in Applied Mechanics and Engineering, April 1, 2026

Stylianos Varchanis and David Stein

Clocks and Dominoes: Timing Mechanisms of Embryogenesis

Nature, January 26, 2026

Yonghyun Song, et al.

Condensation dynamics of sticky and anchored flexible biopolymers

arXiv, December 19, 2025

Adam Lamson, Mohammadhossein Firouznia, and Michael J. Shelley

People

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Michael Shelley

Director, Center for Computational Biology

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Lucas Bouck

Flatiron Research Fellow, Center for Computational Biology

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Chris Edelmaier

Software Engineer, Center for Computational Biology

Portrait photo of Reza Farhadifar

Reza Farhadifar

Research Scientist, Center for Computational Biology

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Gilles Francfort

Research Scientist, Centers for Computational Biology and Mathematics

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Vicente Gomez Herrera

Flatiron Research Fellow, Centers for Computational Biology and Mathematics

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Danyun He

Flatiron Research Fellow, Center for Computational Biology

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Ludwig Hoffmann

Flatiron Research Fellow, Center for Computational Biology

Olenka Jain

Flatiron Research Fellow, Center for Computational Biology

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Ido Lavi

Associate Research Scientist, Center for Computational Biology

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Ursy Makanga

Flatiron Research Fellow, Center for Computational Biology

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Henry Mattingly

Associate Research Scientist, Center for Computational Biology

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Daniel Needleman

Senior Research Scientist, Center for Computational Biology

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Toshi Parmar

Flatiron Research Fellow, Center for Computational Biology

Portrait photo of David Stein

David Stein

Research Scientist, Center for Computational Biology

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Scott Weady

Associate Research Scientist, Center for Computational Biology

Software & Datasets

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aLENS

Software
Simulates microtubule assemblies with motor proteins using Monte Carlo dynamics, constrained collision handling, and massive parallelization.
Colorful circular graphic with pink and teal geometric shapes, yellow connecting lines, and green border. The word MUNDY appears in blue letters along the lower left edge.

MuNDy

Software
A C++ infrastructure for building scalable, biologically grounded microscale multibody dynamics software.
The letters PFI in bold black sans-serif font.

PFI

Software
Probability Flow Inference (PFI) is a framework for inferring gene-regulatory dynamics from time-stamped cross-sectional omics data, where cells are measured destructively and cannot be tracked individually.
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SkellySim

Software
Scalable simulation package for cellular components using parallel computing and fast hydrodynamic methods for filaments, motors, and rigid bodies.

Job Openings

Posted
Section
Computational Biology
For
Postdoctoral Researcher
Type
Fixed Term / Temporary
Area
Research/Science
About
The Center for Computational Biology (CCB) of the Simons Foundation’s Flatiron Institute is actively seeking enthusiastic, full-time post-doctoral Flatiron Research Fellows to join its Biophysical Modeling and Genomics groups. The start date is flexible, with the Fellow expected to begin no later than September 2027. Applications will be reviewed…
Posted
Section
Computational Biology
For
Postdoctoral Researcher
Type
Fixed Term / Temporary
Area
Research/Science
About
The Center for Computational Biology (CCB), an in-house research center of the Simons Foundation’s Flatiron Institute,  is actively seeking enthusiastic, full-time post-doctoral Flatiron Research Fellows to join its Biophysical Modeling Group. The start date is flexible, with the Fellow expected to begin no later than September 2027. Applications…