The advent of the edge computing network paradigm places the computational and storage
resources away from the data centers and closer to the edge of the network largely …

Motifs and degree distribution in transcriptional regulatory networks play an important role
towards their fault-tolerance and efficient information transport. In this paper, we designed …

Biological networks carry out vital functions necessary for sustenance despite environmental
adversities. Transcriptional Regulatory Network (TRN) is one such biological network that is …

We examine and compare transcriptional networks extracted from the bacterium Escherichia
coli and the baker's yeast Saccharomyces cerevisiae using discrete event simulation based …

Machine learning techniques may be useful in determining the features contributing to some
biological properties, such as robustness, which is the tendency for biological systems to …

Motifs and degree distribution in transcriptional regulatory networks play an important role
towards their faulttolerance and efficient information transport. In this paper, we designed an …

Most naturally occurring complex networks exhibit a power-law-based degree distribution. In
such networks, most of the nodes possess the same few lowest degrees (mostly degrees of …

Evolved biological network topologies may resist perturbances to allow for more robust
information transport across larger networks in which their network motifs may play a …

Network growing mechanisms are used to construct random networks that have structural
behaviors similar to existing networks such as genetic networks, in efforts of understanding …

Biological networks are now studied extensively by researchers to understand the working
principles of nature. Machine learning techniques can be useful in realizing the features …