Biosociolink: A decision support system for analyzing link properties in biological and social networks

Abstract

Network based data representation has received widespread attention over the years. Data is oriented in graph format by aligning information as nodes and edges. Some of the predominant network cases include biological and social sciences. There is a growing need to extract knowledge patterns from network orientations. In such scenario, the current study focuses on extracting data patterns from network data. Schizophrenia gene data and TRAI wireless performance data is identified for performing biological and social network analysis. Biological network analysis is performed to identify relevant gene ties which act as hotspots for identifying disease causing genes. On similar lines, social network analysis is performed on wireless dataset to identify essential telecom operators responsible for customer retention. Based on these outcomes, a decision support system, BioSocioLink is designed in R programming language to perform biological and social network analysis. The support system accurately detects knowledge patterns from both the datasets. The study is concluded by deploying the support system in local programming environment.