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Missed our recent webinar on accelerating Computational Fluid Dynamics (CFD) with high-performance computing? The full set of recorded presentations from “Unlocking CFD Performance at Scale with Ansys Fluent and the Flemish Supercomputer Center (VSC)”  is now available online. This webinar brought together experts from industry and academia to demonstrate how modern HPC infrastructure and GPU acceleration are transforming CFD workflows—enabling faster simulations, improved sc

This study benchmarks single-cell chromatin accessibility technologies for training deep learning models in regulatory genomics. Using large-scale datasets from mouse and Drosophila, it shows that increasing dataset size can offset lower per-cell coverage. The optimized HyDrop v2 protocol enables cost-efficient, high-quality data generation, supporting robust sequence-to-function modeling powered by high-performance computing.

Brain activity measured with EEG offers a non-invasive way to study cognitive function. This research uses machine learning and brain connectivity patterns to detect Alzheimer’s disease and frontotemporal dementia, two conditions that are difficult to distinguish clinically. The approach improves diagnostic insights while highlighting the role of brain networks in neurodegenerative disorders.

STREAM-PRS is a multi-tool pipeline that computes and compares polygenic risk scores using five widely used methods. It standardizes scores, applies population structure correction, and selects the best-performing model based on variance explained and predictive performance. The framework improves reproducibility and portability of PRS analyses across datasets and research settings.

Researchers used population pharmacokinetic modeling and Monte Carlo simulations to optimize fluconazole dosing in critically ill patients. By analyzing data from multiple studies, the work identifies body weight and continuous renal replacement therapy (CRRT) as key factors influencing drug exposure and proposes a model-informed dosing strategy to improve target attainment in intensive care settings.

Cancer cells evolve over time through genetic mutations that enable them to adapt, survive therapy, and become drug resistant. Understanding these evolutionary processes at high resolution is essential for developing more effective, targeted cancer treatments.

Schistosomiasis is a snail-borne parasitic disease affecting over 200 million people worldwide. This study examines how schistosome species, parasite development, and co-infection influence the microbiome of the freshwater snail Biomphalaria glabrata. Using 16S rRNA gene metabarcoding, it reveals species-specific microbiome disruption, developmental timing effects, and a stabilizing role of certain co-infections in host–parasite–microbiome interactions.

Mammalian cells can increase the activity of the remaining copy of a gene when the other is deleted. This study shows that the active X chromosome performs this compensation on a gene-by-gene basis at both RNA and protein levels. The work clarifies how cells maintain balanced gene expression and reveals a broader, though limited, compensatory capacity across the genome.