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• W4380080384 abstract "Abstract The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation. Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMus in terms of TF targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs." @default.
• W4380080384 created "2023-06-10" @default.
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• W4380080384 date "2023-06-09" @default.
• W4380080384 modified "2023-10-13" @default.
• W4380080384 title "Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS" @default.
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• W4380080384 doi "https://doi.org/10.1101/2023.06.09.543828" @default.
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