Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Combinational logic network for digitally coded gene expression of gastric cancer

Authors
Park, S.Nam, S.
Issue Date
2017
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Boolean models; Cancer; Logical networks; Network models
Citation
Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016, pp.1777 - 1782
Journal Title
Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
Start Page
1777
End Page
1782
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6635
DOI
10.1109/BIBM.2016.7822788
ISSN
0000-0000
Abstract
In general, Boolean networks have been addressed in time-series datasets. However, in the recent field of next-generation sequencing-based cancer genomics, cross-sectional data sets having enormous numbers of patients have been accumulated. Here, we deal with representation of cross-sectional datasets using Boolean networks, and specifically, combinational logic network approach. We then applied the approach to a real cancer patient dataset, demonstrating the feasibility of using Boolean networks in graphical representation of cross-sectional datasets. © 2016 IEEE.
Files in This Item
There are no files associated with this item.
Appears in
Collections
바이오나노대학 > 생명과학과 > 1. Journal Articles
약학대학 > 약학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Park, Sung Jean photo

Park, Sung Jean
Pharmacy (Dept.of Pharmacy)
Read more

Altmetrics

Total Views & Downloads

BROWSE