Proceedings of the 2015 International Conference on Mechanical Science and Engineering

A Data Mining Method to Find Differentially Expressed miRNAs Using Access Database Language

Authors
Yafen Chen, Xiaoai Chen, Rong Wang, Yiwei Wang, Ping Zhou, Ke Wang
Corresponding Author
Yafen Chen
Available Online March 2016.
DOI
10.2991/mse-15.2016.43How to use a DOI?
Keywords
database language, data mining, breast cancer, miRNA
Abstract

Objective We use database language for data mining in order to find differentially expressed miRNAs. Methods We first construct the E-R model, then the data were converted into the appropriate format, and the converted data were imported into the database accurately. In the end, we extracted the data and carried out statistical analysis. Results MicroRNA's t test data show that there are differences of miRNA expressions between breast cancer patients of different nationalities. Conclusion Access database language can effectively assist data mining, and facilitates data for further mathematical analysis.

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 2015 International Conference on Mechanical Science and Engineering
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
10.2991/mse-15.2016.43
ISSN
2352-5401
DOI
10.2991/mse-15.2016.43How 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  - Yafen Chen
AU  - Xiaoai Chen
AU  - Rong Wang
AU  - Yiwei Wang
AU  - Ping Zhou
AU  - Ke Wang
PY  - 2016/03
DA  - 2016/03
TI  - A Data Mining Method to Find Differentially Expressed miRNAs Using Access Database Language
BT  - Proceedings of the 2015 International Conference on Mechanical Science and Engineering
PB  - Atlantis Press
SP  - 251
EP  - 254
SN  - 2352-5401
UR  - https://doi.org/10.2991/mse-15.2016.43
DO  - 10.2991/mse-15.2016.43
ID  - Chen2016/03
ER  -