1225-ExpiMap: for Single-Cell Reference Mappingc
The paper introduces expiMap, a specialized deep-learning architecture designed to improve the interpretation and integration of single-cell genomics data. By incorporating biologically informed gene programs into its structure, the model allows researchers to map new data into reference atlases using understandable categories like pathways instead of abstract variables. ExpiMap excels at identifying specific biological responses to diseases, such as COVID-19 and diabetes, and can even discover novel gene programs not previously recorded in databases. It effectively balances complex data…
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