News
07/2025
Ourpaper entitled "DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads" was recently accepted at Nature Communications.
06/2025
Ourpaper entitled "A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases" was recently accepted at Nature Biomedical Engineering.
05/2025
Dr. Jun Ding receivedFRQS Junior 2 Award from the Fonds de recherche du Québec – Santé (FRQS).
Ourpaper entitled "Harnessing agent-based frameworks in CellAgentChat to unravel cell-cell interactions from single-cell and spatial transcriptomics" was recently accepted at Genome Research.
Ourpaper entitled "SUICA: Learning Super-high Dimensional Sparse Implicit Neural Representations for Spatial Transcriptomics" was recently accepted at Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
04/2025
Ourpaper entitled "Efficient and scalable construction of clinical variable networks for complex diseases with RAMEN" was recently accepted at Cell Reports Methods.
02/2025
Ourpaper entitled "scCobra allows contrastive cell embedding learning with domain adaptation for single cell data integration and harmonization" was recently accepted at Communications Biology.
01/2025
Ourpaper entitled "Single-Cell Multi-Omics Profiling of Immune Cells Isolated from Atherosclerotic Plaques in Male ApoE Knockout Mice Exposed to Arsenic" was recently accepted at Environmental Health Perspectives.
12/2024
Recently, our new toolsscSemiProfiler,CellAgentChat andUNAGI have been highlighted byNATURE TECHNOLOGY FEATURE! We are glad to contribute to the computational technologies of the Human Cell Atlas that are poised to enable the next set of discoveries.
10/2024
Introducing MATES! A deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. This development facilitates the exploration of single-cell heterogeneity and gene regulation through the lens of TEs, offering an effective transposon quantification tool for the single-cell genomics community.
07/2024
Introducing scCross! A tool leveraging variational autoencoders, generative adversarial networks, and the mutual nearest neighbors (MNN) technique for modality alignment. By enabling single-cell cross-modal data generation, multi-omics data simulation, and in silico cellular perturbations, scCross enhances the utility of single-cell multi-omics studies.
07/2024
Introducing scSemiProfiler! Our new tool in Nature Communications uses AI to "semi-profile" single-cell data at 1/10 to 1/3 of the cost, with near-identical results to real-profiled data. We're also building a cloud service for easy access.
09/2023
Welcome all the new students that have joined this big lab family this year!
10/2021
Our paper entitled "Temporal modeling using single cell transcriptomics" was recently accepted at Nature Reviews Genetics
08/2021
Our paper entitled "Computational tools for analyzing single cell data in pluripotent cell differentiation studies" was recently accepted at Cell Reports Methods.
08/2021
Our paper entitled "A versatile model for single-cell data analysis" was recently published at Nature Computational Science.
08/2020
Ding Lab actively seeks talented and motivated Ph.D., Master, and Undergraduate students who share our passion for single genomics and machine learning applications in health science. Please check here for details.
