Data for: TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle

This repository contains the raw and processed data analyzed in: TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle. Guerra et al. 2022 Version 1

Matlab code.zip from Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter

Matlab scripts and functions necessary to reproduce the results of the pape

Matlab code.tar from Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter

Matlab scripts and functions necessary to reproduce the results of the pape

Biometric Recognition of African Clawed Frogs

The dataset of African Claw Frogs consists of 1,647 images for 160 classes, with an average of 10.3 images per class. The frogs are housed in the University of Groningen, following animal welfare laws and approved by the relevant authorities. The frogs are divided into groups of ten to twenty individuals in aquatic tanks. To capture the images, the frogs are placed individually in transparent containers filled with water on a white surface. The setup takes into account the frogs' pigment changes by housing them in transparent boxes on a yellow surface for approximately 24 hours before photography. The pictures are taken using at least four different smartphones per frog, ensuring consistency in angle and distance from the camera to the container. The dataset includes images taken at different times of day, on different days, and with cameras of different smartphones to enhance the model's robustness. The dataset also provides information on the distribution of samples per frog and the number of photos taken per phone. This dataset has been used to develop an automatic pattern recognition system that is able to determine the individual frogs based on the analysis of their patterns extracted form the iamges. The developed algorithms are very effective and achieve more than 99% recognition rate. (2023-07-07

Additional file 2 of Parameter inference for stochastic single-cell dynamics from lineage tree data

A ZIP file containing the raw datasets obtained from the MCMC runs presented. (ZIP 449 kb

Peer-reviewed dataset: The quantitative and condition-dependent Escherichia coli proteome

Measuring precise concentrations of proteins can provide insights into biological processes. Here we use efficient protein extraction and sample fractionation, as well as state-of-the-art quantitative mass spectrometry techniques to generate a comprehensive, condition-dependent protein-abundance map for Escherichia coli. We measure cellular protein concentrations for 55% of predicted E. coli genes (>2,300 proteins) under 22 different experimental conditions and identify methylation and N-terminal protein acetylations previously not known to be prevalent in bacteria. We uncover system-wide proteome allocation, expression regulation and post-translational adaptations. These data provide a valuable resource for the systems biology and broader E. coli research communities. SpeciesList: scientific name: Escherichia coli; NCBI TaxID: 562; ModificationList: Oxidation; Acetyl; Carbamidomethyl Instrument: LTQ Orbitrap Elite Cell Type: permanent cell line cell Instrument: LTQ Orbitrap Elite Software: Mascot Parser 2.4.3.0, Mascot Server 2.4.1 Modification: Acetyl; Oxidation; Carbamidomethyl Quantification: TIC Experiment Type: Shotgun proteomic

Additional file 2 of Parameter inference for stochastic single-cell dynamics from lineage tree data

A ZIP file containing the raw datasets obtained from the MCMC runs presented. (ZIP 449 kb