Our paper Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data is accepted by Lancet Digital Health. We have developed and validated an innovative deep learning model to predict a patient's long-term outcome after receiving a liver transplant with over 80% accuracy.
Our paper simATAC: a single-cell ATAC-seq simulation framework is accepted by Genome Biology. simATAC is a framework provided as an R package that generates a single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) count matrix, highly resembling real scATAC-seq datasets in library size, sparsity, and averaged chromatin accessibility signals. simATAC provides a robust and systematic approach to generate in silico scATAC-seq samples with cell labels for a comprehensive tool assessment.
Our paper Genotyping SARS-CoV-2 through an interactive web application is accepted by Lancet Digital Health. We provide the COVID-19 Genotyping Tool (CGT), which offers an online, user-friendly platform where researchers can compare the genome sequence of the SARS-CoV-2 virus in their hospital against the global picture.
Chris Mcintosh and Bo Wang won the PMCC Innovation Award for their proposal of an AI-based automatic coronary artery interpretation system. Congratulations!
Bo Wang was invited to present his work “Integrative Network Analysis for Single-cell RNA-seq and Beyond” at the National Research Council, Ottawa.