Package: iPRISM
Type: Package
Title: Intelligent Predicting Response to Cancer Immunotherapy Through
        Systematic Modeling
Version: 0.1.1
Authors@R: c(
    person("Junwei","Han", role = c("aut", "cre", "ctb"),
      email = "hanjunwei1981@163.com"),
    person("Yinchun", "Su", role = "aut"),
    person("Siyuan", "Li", role = "aut"))
Maintainer: Junwei Han <hanjunwei1981@163.com>
Description: Immunotherapy has revolutionized cancer treatment, but
        predicting patient response remains challenging. Here, we
        presented Intelligent Predicting Response to cancer
        Immunotherapy through Systematic Modeling (iPRISM), a novel
        network-based model that integrates multiple data types to
        predict immunotherapy outcomes. It incorporates gene
        expression, biological functional network, tumor
        microenvironment characteristics, immune-related pathways, and
        clinical data to provide a comprehensive view of factors
        influencing immunotherapy efficacy. By identifying key genetic
        and immunological factors, it provides an insight for more
        personalized treatment strategies and combination therapies to
        overcome resistance mechanisms.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
Depends: R (>= 4.1.0)
Imports: ggplot2, Hmisc, tidyr, igraph, pbapply, Matrix, methods
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-04 01:31:56 UTC; root
Author: Junwei Han [aut, cre, ctb], Yinchun Su [aut], Siyuan Li [aut]
Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libuv1-dev
        libxml2-dev
Repository: https://hanjunwei-lab.r-universe.dev
Date/Publication: 2024-07-15 02:47:14 UTC
RemoteUrl: https://github.com/cran/iPRISM
RemoteRef: HEAD
RemoteSha: 4c4a68f55ebf4eda665b467b2450a26dbeb608a8