{ "_id": "6a1af6201d7bb097a09f9ad0", "Package": "SIMLR", "Version": "1.39.0", "Date": "2026-03-09", "Title": "Single-cell Interpretation via Multi-kernel LeaRning (SIMLR)", "Authors@R": "c(person(\"Daniele\", \"Ramazzotti\", role=c(\"aut\"),email=\"daniele.ramazzotti@unimib.it\",\ncomment = c(ORCID = \"0000-0002-6087-2666\")),\nperson(\"Bo\", \"Wang\", role=c(\"aut\"), email=\"wangbo.yunze@gmail.com\"),\nperson(\"Luca\", \"De Sano\", role=c(\"cre\",\"aut\"), email=\"luca.desano@gmail.com\",\ncomment = c(ORCID = \"0000-0002-9618-3774\")),\nperson(\"Serafim\", \"Batzoglou\", role=c(\"ctb\")))", "Description": "Single-cell RNA-seq technologies enable high throughput\ngene expression measurement of individual cells, and allow the\ndiscovery of heterogeneity within cell populations. Measurement\nof cell-to-cell gene expression similarity is critical for the\nidentification, visualization and analysis of cell populations.\nHowever, single-cell data introduce challenges to conventional\nmeasures of gene expression similarity because of the high\nlevel of noise, outliers and dropouts. We develop a novel\nsimilarity-learning framework, SIMLR (Single-cell\nInterpretation via Multi-kernel LeaRning), which learns an\nappropriate distance metric from the data for dimension\nreduction, clustering and visualization.", "Encoding": "UTF-8", "License": "file LICENSE", "URL": "https://github.com/BatzoglouLabSU/SIMLR", "BugReports": "https://github.com/BatzoglouLabSU/SIMLR", "biocViews": "ImmunoOncology, Clustering, GeneExpression, Sequencing,\nSingleCell", "RoxygenNote": "7.3.3", "NeedsCompilation": "yes", "VignetteBuilder": "knitr", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:44:18 UTC", "RemoteUrl": "https://github.com/bioc/SIMLR", "RemoteRef": "HEAD", "RemoteSha": "dd6fe994a67929d10433f2b53737d6dc1a3155ce", "Packaged": { "Date": "2026-05-30 09:46:53 UTC", "User": "root" }, "Author": "Daniele Ramazzotti [aut] (ORCID:\n),\nBo Wang [aut],\nLuca De Sano [cre, aut] (ORCID:\n),\nSerafim Batzoglou [ctb]", "Maintainer": "Luca De Sano ", "MD5sum": 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