iPRISM: Intelligent Predicting Response to Cancer Immunotherapy Through Systematic Modeling

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.

Package details

AuthorJunwei Han [aut, cre, ctb], Yinchun Su [aut], Siyuan Li [aut]
MaintainerJunwei Han <hanjunwei1981@163.com>
LicenseGPL (>= 2)
Version0.1.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("iPRISM")

Try the iPRISM package in your browser

Any scripts or data that you put into this service are public.

iPRISM documentation built on Sept. 11, 2024, 7:14 p.m.