{ "_id": "6a101cf1acfb0bcc41c88a32", "Package": "BioTransition", "Type": "Package", "Title": "Dynamic Network Biomarker Analysis for Critical Transitions", "Version": "2.0.0", "Date": "2026-01-23", "Authors@R": "c(\nperson(\"Zaoqu\", \"Liu\",\nemail = \"liuzaoqu@163.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-0452-742X\")),\nperson(\"Chuhan\", \"Zhang\",\nrole = \"ctb\",\ncomment = \"MDNB implementation\"))", "Description": "A comprehensive toolkit for detecting critical transitions\nand identifying dynamic network biomarkers (DNB) in biological\nsystems. Critical transitions, characterized by sudden shifts\nbetween distinct states, are prevalent in complex biological\nprocesses including disease progression, cellular\ndifferentiation, and developmental transitions. This package\nimplements seven complementary DNB methodologies: (1)\nconventional DNB (cDNB) based on the original DNB theory (Chen\net al. 2012 ); (2) topological DNB\n(tDNB), a novel approach utilizing network topology and\nscale-free properties; (3) landscape DNB (LDNB) for quantifying\nstate transitions (Liu et al. 2019 );\n(4) local DNB (LcDNB) leveraging protein-protein interaction\nnetworks; (5) module-based DNB (MDNB) for modular analysis (Li\net al. 2022 ); (6) time-series\nnetwork module biomarker (TSNMB) for temporal dynamics (Zhong\net al. 2022 ); and (7) time-series\nleading edge (TSLE) analysis (Liu et al. 2020\n). Core computational\nroutines are implemented in C++ via 'Rcpp' for optimal\nperformance. Compatible with bulk RNA-seq, single-cell RNA-seq,\nand spatial transcriptomics data. Includes curated\nprotein-protein interaction networks for human and mouse from\nthe STRING database.", "License": "GPL (>= 3) + file LICENSE", "URL": "https://github.com/SolvingLab/BioTransition,\nhttps://zaoqu-liu.r-universe.dev/BioTransition", "BugReports": "https://github.com/SolvingLab/BioTransition/issues", "biocViews": "Software, StatisticalMethod, Network, SystemsBiology,\nGeneExpression, Transcriptomics, SingleCell, Spatial,\nBiomedicalInformatics, DifferentialExpression", "Encoding": "UTF-8", "ByteCompile": "true", "LazyData": "true", "LazyDataCompression": "xz", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "RoxygenNote": "7.3.3", "Roxygen": "list(markdown = TRUE)", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev", "Repository": "https://zaoqu-liu.r-universe.dev", "Date/Publication": "2026-01-22 20:15:25 UTC", "RemoteUrl": "https://github.com/SolvingLab/BioTransition", "RemoteRef": "HEAD", "RemoteSha": "9168d50e451c54ba739812a2f46a4ff5d05d9cbe", 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