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Disease Pathway Cut for Multi-Target drugs

Authors
 Sunjoo Bang  ;  Sangjoon Son  ;  Sooyoung Kim  ;  Hyunjung Shin 
Citation
 BMC BIOINFORMATICS, Vol.20(1) : 74, 2019 
Journal Title
BMC BIOINFORMATICS
Issue Date
2019
MeSH
Algorithms* ; Disease/genetics* ; Disease Progression ; Drug Development* ; Humans ; Software
Keywords
Directed PPI ; Disease pathway ; Min-cut algorithm ; Pathway network ; Target gene identification
Abstract
BACKGROUND: Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity. But still, the set of target genes should effectively block all possible paths of disease progression.

METHODS: In this article, we propose a network based computational analysis for target gene identification for multi-target drugs. The min-cut algorithm is employed to cut all the paths from onset genes to apoptotic genes on a disease pathway. If the pathway network is completely disconnected, development of disease will not further go on. The genes corresponding to the end points of the cutting edges are identified as candidate target genes for a multi-target drug.

RESULTS AND CONCLUSIONS: The proposed method was applied to 10 disease pathways. In total, thirty candidate genes were suggested. The result was validated with gene set enrichment analysis software, PubMed literature review and de facto drug targets.
Files in This Item:
T201901055.pdf Download
DOI
10.1186/s12859-019-2638-3
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Soo Young(김수영) ORCID logo https://orcid.org/0000-0002-8919-3456
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/169377
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