Literature DB >> 33459772

SubtypeDrug: a software package for prioritization of candidate cancer subtype-specific drugs.

Xudong Han1, Qingfei Kong2, Chonghui Liu2, Liang Cheng1, Junwei Han1.   

Abstract

SUMMARY: Cancer can be classified into various subtypes by its molecular, histological, or clinical characteristics. Discovering cancer-subtype-specific drugs is a crucial step in personalized medicine. SubtypeDrug is a system biology R-based software package that enables the prioritization of subtype-specific drugs based on cancer expression data from samples of many subtypes. This provides a novel approach to identify the subtype-specific drug by considering biological functions regulated by drugs at the subpathway level. The operation modes include extraction of subpathways from biological pathways, identification of dysregulated subpathways induced by each drug, inference of sample-specific subpathway activity profiles, evaluation of drug-disease reverse association at the subpathways level, identification of cancer-subtype-specific drugs through subtype sample set enrichment analysis, and visualization of the results. Its capabilities enable SubtypeDrug to find subtype-specific drugs, which will fill the gaps in the recent tools which only identify the drugs for a particular cancer type. SubtypeDrug may help to facilitate the development of tailored treatment for patients with cancer.
AVAILABILITY AND IMPLEMENTATION: The package is implemented in R and available under GPL-2 license from the CRAN website (https://CRAN.R-project.org/package=SubtypeDrug). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2021). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2021        PMID: 33459772     DOI: 10.1093/bioinformatics/btab011

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

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6.  Graph Embedding Based Novel Gene Discovery Associated With Diabetes Mellitus.

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  8 in total

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