arXiv subjects

Krishanu Deyasi

Publications and source records attributed to Krishanu Deyasi.

5 recordsLinked to original sources

arXiv2024

Analyzing Player Involvement in the Indian Pro Kabaddi League: A Network Analysis Approach

This paper aims to apply network analysis to all players who have participated in the Indian Pro Kabaddi League since its inception. The Kabaddi network has been constructed based on the number of teams and players they have played with. The players have been ranked with the help of the degree and PageRank algorithm. Small-world phenomenon is observed in the Kabaddi network. The significance of the player performance has been compared with the player rank received by the network analysis.

physics.soc-ph↗

arXiv2016

Network similarity and statistical analysis of earthquake seismic data

We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We calculate the conditional probability of the forthcoming occurrences of earthquakes in each region. The conditional probability of each event has been compared with their stationary distribution.

physics.geo-ph↗

arXiv2016

On the initial value of PageRank

Google employs PageRank to rank web pages, determining the order in which search results are presented to users based on their queries. PageRank is primarily utilized for directed networks, although there are instances where it is also applied to undirected networks. In this paper, we have applied PageRank to undirected networks, showing that a vertex's PageRank relies on its initial value, often referred to as an intrinsic, non-network contribution. We have analytically proved that when the initial value of vertices is either proportional to their degrees or set to zero, the PageRank values of the vertices become directly proportional to their degrees. Simulated and empirical data are employed to bolster our research findings. Additionally, we have investigated the impact of initial values on PageRank localization.

physics.soc-ph↗

arXiv2015

Phylogeny of Metabolic Networks: A Spectral Graph Theoretical Approach

Many methods have been developed for finding the commonalities between different organisms to study their phylogeny. The structure of metabolic networks also reveal valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyze the phylogeny from these distances. In our analysis, we focus on the species, which belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.

q-bio.MN↗

arXiv2014

Communication on structure of biological networks

Networks are widely used to represent interaction pattern among the components in complex systems. Structures of real networks from differ- ent domains may vary quite significantly. Since there is an interplay be- tween network architecture and dynamics, structure plays an important role in communication and information spreading on a network. Here we investigate the underlying undirected topology of different biological networks which support faster spreading of information and are better in communication. We analyze the good expansion property by using the spectral gap and communicability between nodes. Different epidemic models are also used to study the transmission of information in terms of disease spreading through individuals (nodes) in those networks. More- over, we explore the structural conformation and properties which may be responsible for better communication. Among all biological networks studied here, the undirected structure of neuronal networks not only pos- sesses the small-world property but the same is expressed remarkably to a higher degree than any randomly generated network which possesses the same degree sequence. A relatively high percentage of nodes, in neuronal networks, form a higher core in their structure. Our study shows that the underlying undirected topology in neuronal networks is significantly qualitatively different than the same from other biological networks and that they may have evolved in such a way that they inherit a (undirected) structure which is excellent and robust in communication.

q-bio.QM↗