Computational Biology | Applied Mathematics

Collective Statistical Dynamics in Biophysical Systems

A computational study investigating whether collective Daphnia deviate from random turning behavior using differential modeling and vector analysis.

MATLAB Algorithms Python Tracking Statistical Analysis

TRACKING_ID: DAPHNIA_01

Computational Stack

DATA ACQUISITION

High-fidelity recording of Daphnia in 15cm petri dishes. Processed using TRex to extract coordinate data.

VECTOR ANALYSIS

Python models used to quantify displacement and trajectory paths from raw .pv files.

DIFFERENTIAL MODELING

Implemented MATLAB algorithms to compute "Cumulative Angle" (φ) via velocity vectors:

dφ = (vx*dvy - vy*dvx) / (vx² + vy²)

Results: Emergent Symmetry Breaking

By analyzing the cumulative angle plots across 50+ trials, we identified a distinct behavioral divergence between isolated individuals and groups.

Isolated Behavior

Single Daphnia showed no discernible trend. Behavior was randomized and unstructured, consistent with Brownian-like motion.

Collective Behavior

Groups exhibited consistent rotational bias (Clockwise/CCW). This "handedness" emerged dynamically from group interaction, not hardwired biology.

Future Directions

The research group is currently expanding on my foundational work by introducing a Multi-Axis Behavior Rig to map 3D dynamics (X-Z plane). We are also utilizing SLEAP.AI for morphometric pose estimation to determine if physical body asymmetry drives the observed rotational bias.

Research Output Console

~/repo/biophysics-pipeline

GitHub Repository

Contains tracking scripts, vector analysis notebooks, and data tracking logs.

Language Python 90%

Tools MATLAB / TRex

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Research Poster

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D. Young, A. Lin, S. Alvarado, O. Kogan. "Collective Behavior of Daphnia." CUNY Queens College, 2024. Reproduced with permission of all co-authors.