Predictive cognitive maps can be learned during behavior and replays using in spiking neurons.

The combination of theoretical modeling and quantitative live imaging revealed that the repressor proteins work cooperatively or anti-cooperatively depending on enhancer architecture.

A physiological mathematical model of chronic myeloid leukemia, validated by experiments in transgenic mice and clinical data, identifies mechanisms underlying the response to tyrosine kinase inhibitor therapy, predicts biomarkers of primary resistance, and suggests new strategies to improve treatment outcomes.

Applying deep learning tools to pinpoint predictive gaps in behavioral cognitive modeling.

New modelling, statistics, and experiments show that cellular populations of mitochondrial DNA (mtDNA) evolve during development according to solvable stochastic dynamics involving binomial partitioning and random turnover, facilitating a predictive and quantitative theory of the mtDNA bottleneck.

A large collaborative project combined many different researchers' forecasts of COVID-19 across Europe, making predictions used in policy more reliable.

Despite the overall impact of COVID-19-related cervical cancer screening disruptions on cervical cancer outcomes being small, disruptions disproportionately affect underscreened women, underpinning the importance of reaching such women as a critical area of focus, regardless of temporary disruptions.

The P300, an electroencephalography (EEG) component known to be evoked by surprising events, predicts learning in a bidirectional manner that depends critically on the surrounding statistical context.

A brain chart database, containing functional and structural normative models, was tested to compare normative modeling features to raw features across three benchmarking tasks including group difference testing, classification, and regression.

Deficiencies of several DNA damage response genes can be predicted by their association with genome-wide mutation patterns.