A combinational logic network based on binarised gene expression in gastric cancer

Citations

WEB OF SCIENCE

2
Citations

SCOPUS

2

초록

In general, gene circuit networks are employed for analysing time-dependent gene expression data sets, known as 'time-series'. However, in analysing cancer genomics data acquired by the recent technology of next-generation sequencing data sets, which are measured once at a particular point in time (static), with enormous numbers of patients have accumulated. Here, we present a combinational logic network, with static gene expression data sets, to combine the structural compositions and all values of samples using Boolean Algebra expression, rather than using representative values. We then attempt to validate this approach by applying it to a real cancer patient data set, demonstrating the feasibility of using combinational logic networks for graphically representing static gene expression data sets.

키워드

Boolean logic model; network model; gastric cancer; MODELS
제목
A combinational logic network based on binarised gene expression in gastric cancer
저자
Park, Sungjin; Nam, Seungyoon
DOI
10.1504/IJDMB.2017.10006245
발행일
2017-07
유형
Article
저널명
International Journal of Data Mining and Bioinformatics
권
17
호
3
페이지
206 ~ 216