Issue |
E3S Web Conf.
Volume 131, 2019
2nd International Conference on Biofilms (ChinaBiofilms 2019)
|
|
---|---|---|
Article Number | 01010 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/e3sconf/201913101010 | |
Published online | 19 November 2019 |
Constructing and analyzing a disease network based on proteins
1
Guangxi Colleges and Universities Key Laboratory of Scientific Computing & Intelligent Information Processing, Nanning Normal University, Nanning 530299, China
2
School of Physical Education and Health, Nanning Normal University, Nanning 530299, China
a Corresponding author: 2313166529@qq.com
Protein is the specific executor of life activities, but there is no protein-based disease network and the current disease networks cannot show that a disease group share the same factors. We propose a method to construct a protein-based network by assigning disease pairs to different intervals according to their similarities and searching for disease groups in each interval. Statistical methods are used to analyze the disease network, and the result indicates that : in the case where a disease belongs to only one disease group, most diseases have their own protein characteristics, but the common protein of them is not obvious; the more diseases a protein is related to, the more likely the protein becomes common protein; diseases grouping at protein level in this study are different from traditional disease classification; there is a certain relationship between disease symptoms and underlying proteins, but not one-to-one correspondence.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.