Biophysical Modeling for Gene Expression and Evolution

Principled biophysical modeling is a necessary foundation for analyzing RNA sequencing data. In recent years, higher quality data for other data modalities at single-cell resolution have become available. I present joint biophysical models combining two of these modalities, chromatin accessibility measurements (ATAC-seq) and protein counts, individually with single-cell transcriptomic data, and give preliminary data results. I consider the extension of biophysically motivated models to the field of phylogenetics. I present competing mechanistic hypotheses for gene expression evolution and test them via parametrized single-cell cross-species data. I also consider a physics-inspired model for population-level evolution via maternal effects and interacting subpopulations.

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Publication Details

Journal
Caltech Library
Published
2026-02-23
DOI
https://doi.org/10.7907/chmp-kt37
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Biophysical Modeling for Gene Expression and Evolution

Catherine Felce
Caltech Library
Single-cell and spatial transcriptomics
article

Biophysical Modeling for Gene Expression and Evolution

Catherine Felce
article en

Abstract

Principled biophysical modeling is a necessary foundation for analyzing RNA sequencing data. In recent years, higher quality data for other data modalities at single-cell resolution have become available. I present joint biophysical models combining two of these modalities, chromatin accessibility measurements (ATAC-seq) and protein counts, individually with single-cell transcriptomic data, and give preliminary data results. I consider the extension of biophysically motivated models to the field of phylogenetics. I present competing mechanistic hypotheses for gene expression evolution and test them via parametrized single-cell cross-species data. I also consider a physics-inspired model for population-level evolution via maternal effects and interacting subpopulations.

Caltech Library
California Institute of Technology (US)
Openalex Percentile: Top 45%
Single-cell and spatial transcriptomics
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