Custom BIAS

Mund et al. have developed a revolutionary method called Deep Visual Proteomics (DVP), which for the first time, allows for the analysis of thousands of proteins from single cells while keeping their original location in the tissue intact. Our Biological Image Analysis Software (BIAS) was a key component of this research, providing the powerful AI-driven image analysis needed to identify and classify cells for proteomic analysis. This groundbreaking work, published in Nature Biotechnology, opens up new avenues for understanding the molecular details of diseases like cancer.

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.