Peter S. Swain

Quantifying the nuclear localisation of fluorescently tagged proteins

The paper develops a convolutional neural network to quantify nuclear localisation of fluorescently tagged proteins in yeast, outperforming existing methods in single-cell time series analysis.

Single-cell metabolic oscillations are pervasive and may alleviate a proteome constraint

The paper shows single-cell metabolic oscillations are widespread in yeast and propose they help overcome proteome limitations by sequentially synthesizing biomass components.

A co-transcriptional mechanism for tightly controlling RNA homeostasis in yeast

The paper shows that the NNS complex regulates RNA homeostasis in yeast by controlling the expression of the mitochondrial transporter Pic2, with defects causing growth defects and stress.

Nunchaku: Optimally partitioning data into piece-wise linear segments

The paper introduces a Bayesian algorithm to optimally partition 2D data into piece-wise linear segments, applied to microbial growth analysis.

The type of carbon source not the growth rate it supports can determine diauxie

This study shows that budding yeast prefer galactose over palatinose despite faster growth on palatinose, challenging the idea that carbon flux-sensing alone determines carbon source preference.

A label-free method to track individuals and lineages of budding cells

This paper introduces BABY, a label-free method to track budding yeast cells and estimate growth rates using machine learning, revealing sizer- and timer-controlled bud growth and Sfp1 dynamics.

A push-pull system of repressors matches levels of glucose transporters to extracellular glucose in budding yeast

The paper shows that budding yeast use a push-pull repression system to dynamically match glucose transporter levels to extracellular glucose concentrations.

Estimating numbers of fluorescent molecules in single cells by analysing fluctuations in photobleaching

The paper develops an algorithm to estimate fluorescent molecule numbers in single cells using photobleaching fluctuations, validated in yeast with Bayesian inference and noise modeling.

Distributed and dynamic intracellular organization of extracellular information

The paper quantifies how extracellular information is encoded in the dynamic nuclear localization of transcription factors in yeast, showing that collective dynamics, not individual factors, represent environmental states.

Morphologically Constrained and Data Informed Cell Segmentation of Budding Yeast

The paper introduces DISCO, a cell segmentation framework for microfluidic devices that improves tracking and segmentation by incorporating physical constraints and morphology, showing better performance than existing software.