Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

A greedy-network-based approach for human disease module identification

Authors
Meng Jin, Zhiyuan Yang, Jianwei Lu, Tianwei Yu
Corresponding Author
Meng Jin
Available Online December 2016.
DOI
https://doi.org/10.2991/iceeecs-16.2016.98How to use a DOI?
Keywords
Gene expression, Biological networks, Greedy algorithm, Machine learning, Cancer biology
Abstract

The accurate classification of disease module from gene expression profiles is quite challenging for new biomarkers because of high noise in gene expression measurements and the small sample size [1]. Studies have shown that network-based gene selection is more reliable than individual genes. Because genes related with same or similar disease modules usually reside in the same vicinity of the molecular network [3]. Based on this theory, we propose a greedy-network-based approach for gene identification. In our study, we use this method in a pediatric acute lymphoblastic leukemia (ALL) [4] dataset and a triple-negative breast cancer (TNBC) microarray dataset. The results show our method achieves higher accuracy in the identification of gene makers.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-265-7
ISSN
2352-538X
DOI
https://doi.org/10.2991/iceeecs-16.2016.98How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Meng Jin
AU  - Zhiyuan Yang
AU  - Jianwei Lu
AU  - Tianwei Yu
PY  - 2016/12
DA  - 2016/12
TI  - A greedy-network-based approach for human disease module identification
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 474
EP  - 478
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.98
DO  - https://doi.org/10.2991/iceeecs-16.2016.98
ID  - Jin2016/12
ER  -