Author name: kriston

Ede Migh and his colleagues have created a high-resolution map of protein changes during cell division, providing a detailed look into the molecular machinery of mitosis. This research, currently available as a preprint on bioRxiv, utilized BIAS to perform the sophisticated image analysis required to track these dynamic processes. The study offers a valuable resource for the scientific community, including an interactive online platform, to explore the complex proteomic landscape of mitotic progression.

Bolck et al. present a novel “Deep Visual Multi-Omics” workflow to characterize the molecular features behind different morphological grades of clear cell renal cell carcinoma (ccRCC). Our Biological Image Analysis Software (BIAS) was a central component of this approach, using artificial intelligence to classify individual cancer cells from pathology slides, which enabled their targeted isolation for deep molecular analysis. This work, available as a preprint, identifies unique molecular signatures of highly aggressive rhabdoid cancer cells, providing a basis for developing new combination therapies.

Diosdi et al. introduce HCS-3DX, a next-generation, AI-driven system designed to overcome the challenges of high-content screening in complex 3D cell cultures. This integrated platform, developed in-house at Single-Cell Technologies, leverages our Biological Image Analysis Software (BIAS) to enable precise, single-cell level analysis of spheroids and organoids, paving the way for more accurate drug discovery and personalized medicine.