Identification of Essential Proteins by Detecting Topological and Functional Clusters in Protein Interaction Network of Saccharomyces Cerevisiae

Identification of Essential Proteins by Detecting Topological and Functional Clusters in Protein Interaction Network of Saccharomyces Cerevisiae

Kaustav Sengupta (Jadavpur University, Kolkata, India), Sovan Saha (Dr. Sudhir Chandra Sur Degree Engineering College, Kolkata, India), Piyali Chatterjee (Netaji Subhash Engineering College, Kolkata, India), Mahantapas Kundu (Department of Computer Science and Engineering, Jadavpur University, Kolkata, India), Mita Nasipuri (Department of Computer Science and Engineering, Jadavpur University, Kolkata, India) and Subhadip Basu (Jadavpur University, Kolkata, India)
Copyright: © 2019 |Pages: 21
DOI: 10.4018/IJNCR.2019010103

Abstract

Essential protein identification is an important factor to inspect the mechanisms of disease progression and to identify drug targets. With the advancement of high throughput genome sequencing projects, a bulk of protein data is available where the analysis of interaction pattern, functional annotation and characterization are necessary for detecting proteins' essentiality in network level. A set of centrality measure has been used to identify the highly connected proteins or hubs. From recent studies, it is observed that the majority of hubs are considered to be essential proteins. In this article, a method EPIN_Pred is proposed where a combination of several centrality measures is used to find the hub and non-hub proteins. Using the cohesiveness property, overlapping topological clusters are found. Using gene ontology (GO) terms, these topological clusters are again combined, if required. The performance of EPIN_Pred is also found to be superior when compared to other state-of-the-art methods.
Article Preview
Top

2. Background

Though many experimental methods, namely, RNA interference (Cullen & Arndt, 2005; Kamath et al., 2003), conditional knockout (Giaever et al., 2002) etc. are reliable to detect essential proteins but they become less promising due to time and cost metric. With the introduction of high throughput techniques such as mass spectrometry, tandem affinity purification (Ho et al., 2002), a deluge of Protein Interaction data is available whose functional characterization is required in large scale. This fact necessitates the computational techniques to predict the function of unknown protein, insight of essential proteins and their interaction pattern which are helpful to discover drug targets.

Form the recent studies it is observed that computational techniques use sequence-based features or topological features or combination of these heterogeneous features to detect essential proteins.

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 9: 4 Issues (2020): 1 Released, 3 Forthcoming
Volume 8: 4 Issues (2019)
Volume 7: 4 Issues (2018)
Volume 6: 2 Issues (2017)
Volume 5: 4 Issues (2015)
Volume 4: 4 Issues (2014)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing