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Q-omics: Smart Software for Assisting Oncology and Cancer Research

Authors
Lee, JieunKim, YoungjuJin, SeongheeYoo, HeeseungJeong, SuminJeong, EunaYoon, Sukjoon
Issue Date
Nov-2021
Publisher
KOREAN SOC MOLECULAR & CELLULAR BIOLOGY
Keywords
biomarker; cancer bioinformatics; immune infiltrate; Kaplan-Meier plot; omics data mining; smart software
Citation
MOLECULES AND CELLS, v.44, no.11, pp 843 - 850
Pages
8
Journal Title
MOLECULES AND CELLS
Volume
44
Number
11
Start Page
843
End Page
850
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/146146
DOI
10.14348/molcells.2021.0169
ISSN
1016-8478
0219-1032
Abstract
The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http:// qomics.sookmyung.ac.kr.
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