Publications
Peer-reviewed articles, preprints, and collaborative research frameworks.
Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data
Heidari, E.*, Moorman, A.*, Unyi, D., et al. bioRxiv, 2025 (under revision Nature Methods).
Lead developer: formulated cell segmentation as a large-scale heterogeneous GNN problem; designed multi-GPU pipeline (10–100M nodes) achieving 1000× speedup.
Integrated in vivo combinatorial functional genomics and spatial transcriptomics of tumours
Breinig, M.*, Lomakin, A.*, Heidari, E.*, et al. Nature Biomedical Engineering, 2025.
Co-lead developer: built end-to-end spatial phenotyping pipeline linking genetic perturbations to tumor microenvironments.
SpatialData: an open and universal data framework for spatial omics
Marconato, L.*, ..., Heidari, E., et al. Nature Methods 22:58–62, 2025.
Contributor: designed multi-layer breast cancer analysis demonstrating universal grammar for multimodal spatial omics.
Supervised spatial inference of dissociated single-cell data with SageNet
Heidari, E., Lohoff, T., et al. bioRxiv, 2022.
Lead developer: introduced graph-attention-based spatial inference; outperformed Tangram and NovoSpaRc.
An end-to-end workflow for high-throughput discovery of clinically relevant insights from large biomedical datasets
Heidari, E., Sadeghi, M.A., et al. bioRxiv, 2020.
Lead developer: designed scalable analytics pipeline for population-scale biomedical data.
snRNA-seq stratifies multiple sclerosis patients into distinct white matter glial responses
Macnair, W., ..., Heidari, E., et al. Neuron 113(3), 2025.
Contributor: architected large-scale sc/snRNA-seq pipelines (1M cells).
Meta-analysis of single-cell method benchmarks reveals the need for extensibility and interoperability
Sonrel, A., ..., Heidari, E., et al. Genome Biology 24:119, 2023.
Contributor: analysis and synthesis of benchmarking results.