Artificial intelligence driven tumor risk stratification from single-cell transcriptomics using phenotype algebra

Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the characterization of phenotypic heterogeneity within tumors. Current scRNA-seq analysis pipelines are capable of identifying a myriad of malignant and non-malignant cell subtypes from single-cell profili...

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গ্রন্থ-পঞ্জীর বিবরন

প্রধান লেখক:	Namrata Bhattacharya, Anja Rockstroh, Sanket Suhas Deshpande, Sam Koshy Thomas, Anunay Yadav, Chitrita Goswami, Smriti Chawla, Pierre Solomon, Cynthia Fourgeux, Gaurav Ahuja, Brett Hollier, Himanshu Kumar, Antoine Roquilly, Jeremie Poschmann, Melanie Lehman, Colleen C Nelson, Debarka Sengupta
বিন্যাস:	Artigo
ভাষা:	Inglês
প্রকাশিত:	eLife Sciences Publications Ltd 2025-06-01
মালা:	eLife
বিষয়গুলি:	single-cell RNA-seq risk stratification transfer learning prostate cancer marker-free language model
অনলাইন ব্যবহার করুন:	https://elifesciences.org/articles/98469
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