Jiangyan Yu

clinTALL is a deep learning framework that classifies pediatric T-ALL subtypes and predicts treatment outcomes using multimodal data, achieving high accuracy and concordance indices.

FA-NIVA provides an automated analysis framework for Nanopore long-read sequencing data to detect SNVs and SVs in Fanconi anemia genes with improved genotyping accuracy.

The paper identifies differences in G protein expression levels between PVM strains, linking these differences to virulence through genetic variations in the G gene.

Shiny-Calorie provides a flexible, open-source tool for analyzing and visualizing indirect calorimetry data, supporting standardized integration and statistical analysis of metabolic phenotyping datasets.

This study identifies a novel inflammation-associated dendritic cell state in human chronic inflammation and shows its spatial restriction and therapeutic relevance.

This study shows that ACC1 regulates adipose ILC2 differentiation and function in obesity, linking lipid metabolism to metabolic health.

This paper introduces Metadatasheet, a metadata standard designed to improve data management by aligning with the data-lifecycle and enabling structured metadata recording in Microsoft Excel.

IntestLine maps rolled intestinal tissue images onto a line to improve visualization and analysis of proximal-distal and serosa-luminal features.