Accurate description of the condition of engineering structures is important for ensuring structural safety. Traditional analysis methods based on simplified physical mechanisms cannot accurately ...

Imaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients ...

Loren Frank's HHMI lab at UCSF has pioneered an ambitious framework for sharing vast neuroscience datasets and complicated analysis methods, a step toward tipping the culture of science toward more ...

To address critical research challenges in heavy-ion collisions at Fermi-energy regimes—specifically targeting the nuclear equation of state (nEoS), Femtoscopic interferometry of light nuclei, and ...

Imagine this: you’ve just received a dataset for an urgent project. At first glance, it’s a mess—duplicate entries, missing values, inconsistent formats, and columns that don’t make sense. You know ...

We analyzed 4,427 patients with MDS divided into training and validation cohorts. Deep learning methods were applied to integrate and impute clinical/genomic features. Clustering was performed by ...

Using an expert consensus-based approach, a netball video analysis consensus (NVAC) group of researchers and practitioners was formed to develop a video analysis framework of descriptors and ...

This article and associated images are based on a poster originally authored by Matthew Chung, William Guesdon, Kai Lawson-McDowall and Matthew Alderdice and presented at ELRIG Drug Discovery 2025 in ...

Unlock the power of your data with an effective data governance framework for security, compliance, and decision-making. Data governance frameworks are structured approaches to managing and utilizing ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...