Development of biological network crawling, clustering and visualization system

Abstract

With the development of software and devices for next generation sequencing, a vast amount of bioinformatics data has been generated recently. Also, bioinformatics data based big-data technology is rising rapidly as a core technology by the bio-informatician, biologist and big-data scientist. Especially, most big data analyses are based on network analyses because it can discover characteristics and patterns between data in a network. However, a biological network analysis requires a lot of time and effort because biological networks are high volume and very diverse. In this paper, we proposed a network crawling, clustering and visualization system that crawls literatures and papers from user interest a web site, constructs a biological network based on a hierarchy structure of biological entities and relations extracted from sentences in the literatures and papers and visualizes relations and interactions of the network by clustering and selecting core nodes from the network. Finally, we construct a Alzheimer's disease network collected from PubMed and show the results on clustering and selecting core nodes from the network.