Discovering low-connectivity essential proteins based on protein-protein interaction network
by Yun-Yuan Dong
International Journal of High Performance Systems Architecture (IJHPSA), Vol. 6, No. 3, 2016

Abstract: Essential proteins are crucial for the survival of cellular life and they are also important for many applications, such as drug design and the defense against human pathogens. Existing experimental approaches to identify essential proteins are time-consuming and expensive. Therefore, many computational methods to predict essential proteins are employed to address this issue. However, most of those approaches focus on topological features of protein-protein interaction (PPI) networks and they often fail to consider the low-connectivity essential proteins. In this paper, we present three indexes to measure biological features of low-connectivity essential proteins. And we also propose a centrality measure interaction-complex-function centrality (ICFC) to predict low-connectivity essential proteins, which combines topological structure information of the PPI network with the distinguishable biological properties of essential proteins. The experimental results demonstrate that the predicted precision of ICFC outperforms ten exiting centrality measures. The improvements of ICFC over the ten exiting centrality measures are up to 1.08∼3.31 times.

Online publication date: Thu, 01-Dec-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of High Performance Systems Architecture (IJHPSA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com