{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["14(1)"],"submitter":["Islam MT"],"pubmed_abstract":["Remarkable advances in single cell genomics have presented unique challenges and opportunities for interrogating a wealth of biomedical inquiries. High dimensional genomic data are inherently complex because of intertwined relationships among the genes. Existing methods, including emerging deep learning-based approaches, do not consider the underlying biological characteristics during data processing, which greatly compromises the performance of data analysis and hinders the maximal utilization of state-of-the-art genomic techniques. In this work, we develop an entropy-based cartography strategy to contrive the high dimensional gene expression data into a configured image format, referred to as genomap, with explicit integration of the genomic interactions. This unique cartography casts th"],"journal":["Nature communications"],"pagination":["679"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9908983"],"repository":["biostudies-literature"],"pubmed_title":["Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data."],"pmcid":["PMC9908983"],"pubmed_authors":["Xing L","Islam MT"],"additional_accession":[]},"is_claimable":false,"name":"Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data.","description":"Remarkable advances in single cell genomics have presented unique challenges and opportunities for interrogating a wealth of biomedical inquiries. High dimensional genomic data are inherently complex because of intertwined relationships among the genes. Existing methods, including emerging deep learning-based approaches, do not consider the underlying biological characteristics during data processing, which greatly compromises the performance of data analysis and hinders the maximal utilization of state-of-the-art genomic techniques. In this work, we develop an entropy-based cartography strategy to contrive the high dimensional gene expression data into a configured image format, referred to as genomap, with explicit integration of the genomic interactions. This unique cartography casts th","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Feb","modification":"2026-03-18T13:46:39.069Z","creation":"2025-04-04T18:43:37.178Z"},"accession":"S-EPMC9908983","cross_references":{"pubmed":["36755047"],"doi":["10.1038/s41467-023-36383-6"]}}