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Title

Computer aided analysis of disease linked protein networks
 

Authors

Soudabeh Sabetian1,2* & Mohd Shahir Shamsir1

 

Affiliation

1Department of Biological and Health Sciences, Faculty of Bioscience & Medical Engineering, Universiti Teknologi Malaysia, 81310 Johor, Malaysia; 2Infertility Research Center, Shiraz University, Shiraz 71454, Iran, Shiraz University of Medical Sciences, Shiraz, Iran

 

Email

Soudabeh Sabetian - E-mail: soudabehsabet@gmail.com; *Corresponding author

 

Article Type

Review Article

 

Date

Received January 21, 2019; Revised April 16, 2019; Accepted April 17, 2019; Published July 31, 2019

 

Abstract

Proteins can interact in various ways, ranging from direct physical relationships to indirect interactions in a formation of protein-protein interaction network. Diagnosis of the protein connections is critical to identify various cellular pathways. Today constructing and analyzing the protein interaction network is being developed as a powerful approach to create network pharmacology toward detecting unknown genes and proteins associated with diseases. Discovery drug targets regarding therapeutic decisions are exciting outcomes of studying disease networks. Protein connections may be identified by experimental and recent new computational approaches. Due to difficulties in analyzing in-vivo proteins interactions, many researchers have encouraged improving computational methods to design protein interaction network. In this review, the experimental and computational approaches and also advantages and disadvantages of these methods regarding the identification of new interactions in a molecular mechanism have been reviewed. Systematic analysis of complex biological systems including network pharmacology and disease network has also been discussed in this review.

 

Keywords

Protein interaction network; disease network; computational method

 

Citation

Sabetian & Shamsir, Bioinformation 15(7): 513-522 (2019)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.