Biomedical Informatics at ETH Zurich
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- sigmoni Public Forked from vikshiv/sigmoni
Nanopore signal-based classification using compressed indexing and matching statistics
- DeepSpot Public
DeepSpot: Deep learning model for predicting spatial transcriptomics from H&E histopathology images. Supports spot-level (Visium) and single-cell (Xenium) resolution.
- aestetik Public
AESTETIK: Convolutional autoencoder for learning spot representations from spatial transcriptomics and morphology data
- DeepSpot2Cell Public
DeepSpot2Cell: Predicting virtual single-cell spatial transcriptomics from H&E images using spot-level supervision
- DeepSpotM Public
Multimodal foundation model predicting transcriptome-wide virtual spatial transcriptomics from histology.
- ReadBouncer Public Forked from JensUweUlrich/ReadBouncer
Fast and scalable nanopore adaptive sampling
- RawHash Public Forked from CMU-SAFARI/RawHash
RawHash can accurately and efficiently map raw nanopore signals to reference genomes of varying sizes (e.g., from viral to a human genomes) in real-time without basecalling. Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440).
- MinknoApiSimulator Public
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