R Sai Prathap Yadav, Paulami Dey ... Pavan Agrawal
A low-cost, portable platform combining machine learning–based classifiers enables accurate quantification of Drosophila aggression and courtship, expanding access to behavioral neuroscience in resource-limited settings.
Jakob Cronshagen, Johannes Allweier ... Tobias Spielmann
The generation of malaria parasites expressing only one of the multiple variants of their most important virulence factor enables the study of different aspects of this virulence factor.
Roman Makarov, Spyridon Chavlis, Panayiota Poirazi
An interactive toolbox for standardizing, validating, simulating, reducing, and exploring detailed biophysical models that can be used to reveal how morpho-electric properties map to dendritic and neuronal outputs.
A novel algorithm allowed for the continuous tracking of neurons throughout early postnatal development, revealing a transition in neural firing statistics coinciding with the onset of behaviour-dependent activity.
An AI-driven computational toolkit, Gcoupler, integrates ligand design, statistical modeling, and graph neural networks to predict endogenous metabolites that allosterically modulate the GPCR–Gα interface and regulate downstream signaling.
A collaborative open-source platform enabling interactive 3D visualization, quantitative evaluation, and expert curation of complex biological morphologies to enhance the quality and reproducibility of large-scale imaging studies.
Pablo Ruiz Cuenca, Fábio N Souza ... Emanuele Giorgi
Step selection functions are a useful tool for analysing fine-scale human movements to understand environmental interactions in the context of infectious disease epidemiology.
Sydney Dimmock, Benjamin MS Exley ... Cian O'Donnell
Bayesian hierarchical models offer powerful statistical tools for neuroscientists to analyze whole-brain cell count data, as demonstrated here using two example datasets from different laboratories.
