Madhav Mani

Bacterial vitamin sharing emerges from a balance between release and uptake

The paper quantifies vitamin B12 synthesis and uptake in bacterial isolates, revealing strategies that govern extracellular B12 availability through a balance between release and uptake.

The Trajectory Statistics of Biological Exploratory Dynamics

The paper explores exploratory dynamics in biological processes, proposing mathematical frameworks like geometric distribution and random walks with resets to model search processes and their outcomes.

The ecological context of enzymatic variation

This study links enzyme sequence variation to functional responses in microbial ecosystems using nitrate reductase as a model, showing predictable sequence-to-activity relationships.

A Statistical Approach to Cellular Resource Allocation Models

The paper uses statistical analysis to uncover growth tradeoffs in E. coli and S. pombe by identifying gene sectors and modeling transcription-translation constraints.

A phase oscillator model of cell cycles reveals nuclear density control in a branched fungal network

The paper models nuclear division in a branching fungal network to show that asynchronous cycles and density-responsive branching stabilize nuclear density.

Stomatal setpoints and environmental responsiveness are sculpted by developmental trajectories

The paper identifies developmental rules governing stomatal patterning in Arabidopsis by analyzing variation across accessions and environmental conditions.

Learning the Shape of Evolutionary Landscapes: Geometric Deep Learning Reveals Hidden Structure in Phenotype-to-Fitness Maps

This paper introduces a geometric deep learning method to model phenotype-to-fitness maps, showing it outperforms linear methods in capturing nonlinear structure and predicting fitness landscapes.

Learning geometric models for developmental dynamics

The paper develops a framework using neural networks to infer a geometric landscape of cellular differentiation from gene expression data, providing an interpretable model of developmental dynamics.

Physical modeling of embryonic transcriptomes identifies collective modes of gene expression

The paper uses single-cell sequencing data and statistical physics methods to identify collective modes of gene expression in early ascidian embryos.

Functional regimes define the response of the soil microbiome to environmental change

The paper uses microcosm experiments and modeling to identify three functional regimes governing soil microbiome responses to pH changes, revealing distinct metabolic dynamics and underlying mechanisms.

Illuminating the uncharacterized regulatory genome of E. coli with massively parallel reporters

The paper identifies regulatory elements and transcription factors in E. coli genes across diverse environments using experimental and computational methods.

A physically inspired approach to coarse-graining transcriptomes reveals the dynamics of aging: multiscale description of gene expressions and a spectral view of aging dynamics

This study applies physics-inspired methods to single-cell RNA sequencing data to uncover multiscale patterns in aging transcriptomes and provides a spectral view of aging dynamics.

Inferring single-cell transcriptomic dynamics with structured latent gene expression dynamics

This paper introduces LatentVelo, a method that improves trajectory inference in single-cell RNA-seq by modeling gene dynamics with neural ODEs and a variational autoencoder, enabling lineage-specific dynamics and batch correction.

Spectral decomposition unlocks ascidian morphogenesis

This paper introduces a framework using spectral decomposition to automatically detect and time morphological processes in ascidian embryos from live imaging data.

A mechanical atlas for Ascidian gastrulation

The paper develops a mechanical atlas for ascidian gastrulation by integrating mathematical models with image data to map spatio-temporal mechanical stresses.

Emergence of a geometric pattern of cell fates from tissue-scale mechanics in the Drosophila eye

This study shows that mechanical forces, not biochemical signals, drive the formation of a regular triangular grid of photoreceptor clusters in the Drosophila eye.

Global Constraints within the Developmental Program of the Drosophila Wing

The paper quantifies phenotypic variation in Drosophila wings and identifies a constrained developmental program that integrates genetic and environmental inputs into a single morphological axis.

EMBEDR: Distinguishing Signal from Noise in Single-Cell Omics Data

EMBEDR assesses the quality of dimensionality reduction in single-cell data, distinguishing signal from noise and enabling cell-wise analysis.

The Wg and Dpp morphogens regulate gene expression by modulating the frequency of transcriptional bursts

This study shows that Wg and Dpp morphogens regulate gene expression by modulating transcriptional burst frequency in Drosophila.

Stochastic gene expression is optimized to drive developmental self organization

The paper shows that stochastic gene expression, specifically in senseless protein output, is critical for developmental self-organization in Drosophila, with genomic location and microRNA regulation influencing noise and sensory pattern formation.

A mechanism for the proliferative control of tissue mechanics in the absence of growth

The paper identifies a mechanism by which cell proliferation generates contractile forces in epithelial tissues without growth, using live imaging and simulations.