Publications
Sensitive detection of rare disease-associated cell subsets via representation learning (Nature Communications)
Original manuscript establishing the framework which laid the groundwork for our biomarker discovery platform ScaiVision. Initially designed for CyTOF data, we have now extended this framework for the integrative analysis of a large variety of data modalities enabling true multimodal analyses crucial for precision medicine.
Comparative immune profiling of acute respiratory distress syndrome patients with or without SARS-CoV-2 infection (Cell Reports Medicine)
In this study, exploiting ScaiVision’s unique sensitivity, we were able to identify an immune population strongly linked to the development of complications from COVID associated with a high mortality rate.
Tracing Endometriosis: Coupling deeply phenotyped, single-cell based Endometrial Differences and AI for disease pathology and prediction
Scailyte’s single-cell atlas reveals key gene changes in endometriosis, offering new insights into pathophysiology, predictive models, and potential treatment targets.
CNN-based learning of single-cell transcriptomes reveals a blood-detectable multi-cancer signature of brain metastasis
Scailyte's pan-cancer brain metastasis signature, derived via single-cell RNA sequencing and ScaiVision AI, enables early detection, prognosis, and targeted therapy.
Single-Cell RNA Sequencing of PBMCs Identified Junction Plakoglobin (JUP) as Stratification Biomarker for Endometriosis
This study aimed to identify unique characteristics in the peripheral blood mononuclear cells (PBMCs) of endometriosis patients and develop a non-invasive early diagnostic tool. Using single-cell RNA sequencing (scRNA-seq), we constructed the first single-cell atlas of PBMCs from endometriosis patients based on 107,964 cells and 25,847 genes.
Single-cell neural network classifiers reveal that PM21 NK cell expansion is dependent on B cell signaling
This study addressed the high variability in allogeneic NK cell expansion by applying ScaiVision to pre-expansion single-cell transcriptomics data. While standard methods failed, our AI approach unexpectedly uncovered a previously unknown supportive role for B cells in NK cell expansion, providing a blueprint for improving cell therapy manufacturing.
White Papers
Scailyte’s ScaiVision performs best-in-class at sample class prediction
ScaiVision performs as the best-in-class algorithm at identifying molecular biomarkers, which accurately predict clinical status of the samples. Analysis with ScaiVision unlocks an unparalleled level of high-resolution and clinically relevant discoveries in single-cell datasets.
AI-driven single-cell data analysis identifies a cell signature predictive of neurotoxicity and clinical response in CAR-T cell therapy of DLBCL
Delve deep into the transformative impact of ScaiVision, Scailyte's pioneering platform, on the realm of CAR-T cell therapy for Diffuse Large B-Cell Lymphoma (DLBCL).
