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: 2024-07-12 06:27:46 UTC; syc
Author: Junwei Han [aut, cre, ctb],
  Yinchun Su [aut],
  Siyuan Li [aut]
Repository: CRAN
Date/Publication: 2024-07-14 12:00:02 UTC
Built: R 4.4.3; ; 2025-12-17 05:12:12 UTC; windows
