Latest News

Discover how researchers at KU Leuven developed Metacontextify, a Python tool that connects marine metagenomic samples with environmental data from the Copernicus program. Supported by VSC's high-performance computing infrastructure, the research enriched environmental metadata and retrieved environmental properties for 684 million marine proteins.

Researchers at VUB developed a patient-relevant orthotopic lung cancer model and combined SEPARATE-Seq with spatial transcriptomics to map the immune landscape of lung tumours. Supported by VSC's high-performance computing infrastructure, the study provides new insights into immune cell behavior and offers a valuable resource for cancer immunology and future therapy development.

Researchers at Ghent University developed a patient-centered approach to detect cancer signals hidden in blood plasma using cell-free RNA (cfRNA). By combining RNA sequencing with large-scale computational analysis, they identified personalized molecular patterns that distinguish cancer patients from healthy individuals, advancing the future of precision oncology and personalized diagnostics.

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.

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.

By Irene Talon · Ph.D. Student at KU Leuven, see authors The Laboratory of Cellular Reprogramming and Epigenetic Regulation (Prof....