Quantitative analysis of social influence and digital piracy contagion with differential equations on networks.

Illegal file sharing of copyrighted contents through popular file sharing networks poses an enormous threat to providers of digital contents, such as, games, softwares, music and movies. Though empirical studies of network effects on piracy is a well-studied domain, the dynamics of peer effect in the context of evolving social contagion has not been enough explored using dynamical models. In this research, we methodically study the trends of online piracy with a continuous ODE approach and differential equations on graphs to have a clear comparative view.

Promote to protect: data-driven computational model of peer influence for vaccine perception.

Vaccine hesitancy and acceptance, driven by social influence, is usually explored by most researchers using exhaustive survey-based studies, which investigate public preferences, fundamental values, beliefs, barriers, and drivers through closed or open-ended questionnaires. Commonly used simple statistical tools do not do justice to the richness of this data. Considering the gradual development of vaccine acceptance in a society driven by multiple local/global factors as a compartmental contagion process, we propose a novel methodology where drivers and barriers of these dynamics are detected from survey participants' responses, instead of heuristic arguments.

How surface and fomite infection affect contagion dynamics: a study with self-propelled particles.

Self-propelled particles have been a tool of choice for many studies for understanding spatial interaction of people and propagation of infectious diseases. Other than the direct contagion process through face-to-face contacts with an infected agent, in some diseases, like COVID-19, the disease can spread by indirect ways, through contaminated object surfaces and puff-clouds created by the infected individual. However, this dual spreading process and the impact of these indirect infections in the entire dynamics are not properly explored.

Emergent correlations in gene expression dynamics as footprints of resource competition.

Genetic circuits need a cellular environment to operate in, which naturally couples the circuit function with the overall functionality of gene regulatory network. To execute their functions, all gene circuits draw resources in the form of RNA polymerases, ribosomes, and tRNAs. Recent experiments pointed out that the role of resource competition on synthetic circuit outputs could be immense.

Computational Model on COVID-19 Pandemic Using Probabilistic Cellular Automata.

Since March, 2020, Coronavirus disease (COVID-19) has been designated as a pandemic by World Health Organization. This disease is highly infectious and potentially fatal, causing a global public health concern. To contain the spread of COVID-19, governments are adopting nationwide interventions, like lockdown, containment and quarantine, restrictions on travel, cancelling social events and extensive testing.

A data-driven understanding of COVID-19 dynamics using sequential genetic algorithm based probabilistic cellular automata.

COVID-19 pandemic is severely impacting the lives of billions across the globe. Even after taking massive protective measures like nation-wide lockdowns, discontinuation of international flight services, rigorous testing etc., the infection spreading is still growing steadily, causing thousands of deaths and serious socio-economic crisis.

Ensuring the spread of referral marketing campaigns: a quantitative treatment.

In marketing world, social media is playing a crucial role nowadays. One of the most recent strategies that exploit social contacts for the purpose of marketing, is referral marketing, where a person shares information related to a particular product among his/her social contacts. When this spreading of marketing information goes viral, the diffusion process looks like an epidemic spread.

Non-genetic heterogeneity, criticality and cell differentiation.

The different cell types in a living organism acquire their identity through the process of cell differentiation in which multipotent progenitor cells differentiate into distinct cell types. Experimental evidence and analysis of large-scale microarray data establish the key role played by a two-gene motif in cell differentiation in a number of cell systems. The two genes express transcription factors which repress each other's expression and autoactivate their own production.

Early signatures of regime shifts in gene expression dynamics.

Recently, a large number of studies have been carried out on the early signatures of sudden regime shifts in systems as diverse as ecosystems, financial markets, population biology and complex diseases. The signatures of regime shifts in gene expression dynamics are less systematically investigated. In this paper, we consider sudden regime shifts in the gene expression dynamics described by a fold-bifurcation model involving bistability and hysteresis.

Phenotypic heterogeneity in mycobacterial stringent response.

Background: A common survival strategy of microorganisms subjected to stress involves the generation of phenotypic heterogeneity in the isogenic microbial population enabling a subset of the population to survive under stress. In a recent study, a mycobacterial population of M. smegmatis was shown to develop phenotypic heterogeneity under nutrient depletion.