Cell clustering can vary wildly depending on algorithm settings like the random seed — even with the exact same data. scICE automatically detects and removes unstable groupings, giving researchers ...
Cell clustering serves as a key task in transcriptomic data analysis, playing a crucial role in cell type annotation, marker gene identification, and the discovery of rare cell populations. With the ...
Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...
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