Related papers: Epistatic models predict mutable sites in SARS-CoV…

We propose a novel numerical method able to determine efficiently and effectively the relationship of complementarity between portions of proteins surfaces. This innovative and general procedure, based on the representation of the molecular…

Accurate modeling of lockdown effects on SARS-CoV-2 epidemic evolution is a key issue in order e.g. to inform health-care decisions on emergency management. The compartmental and spatial models so far proposed use parametric descriptions of…

In this work, we extend our previously developed compartmental SEIQRD model for SARS-CoV-2 in Belgium. We introduce SARS-CoV-2 variants of concern, vaccines, and seasonality in our model, as their addition has proven necessary for modelling…

Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the variants. While…

SARS-CoV-2 has characteristics of wide contagion and quick propagation velocity. To analyse the visual information of it, we build a SARS-CoV-2 Microscopic Image Dataset (SC2-MID) with 48 electron microscopic images and also prepare their…

Protein-protein interaction (PPI) networks have been used to investigate the influence of SARS-CoV-2 viral proteins on the function of human cells, laying out a deeper understanding of COVID--19 and providing ground for drug repurposing…

Understanding the viral dynamics and immunizing antibodies of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for devising better therapeutic and prevention strategies for COVID-19. Here, we present a Bayesian…

With the huge spike in the COVID-19 cases across the globe and reverse transcriptase-polymerase chain reaction (RT-PCR) test remains a key component for rapid and accurate detection of severe acute respiratory syndrome coronavirus 2…

Physiological solvent flows surround biological structures triggering therein collective motions. Notable examples are virus/host-cell interactions and solvent-mediated allosteric regulation. The present work describes a multiscale approach…

Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antiviral treatments. In this work, based on the concept of virus…

The COVID-19 crisis called for rapid reaction from all the fields of biomedical research. Traditional drug development involves time consuming pipelines that conflict with the urgence of identifying effective therapies during a health and…

The outbreak of mutant strains and vaccination behaviors have been the focus of recent epidemiological research, but most existing epidemic models failed to simultaneously capture viral mutation and consider the complexity and behavioral…

The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome -- millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of…

Facing a global challenge with over 6.9 million fatalities, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of CoViD-19, demands novel and comprehensive approaches to understand its complex dynamics. This…

Mechanistic models fit to streaming surveillance data are critical to understanding the transmission dynamics of an outbreak as it unfolds in real-time. However, transmission model parameter estimation can be imprecise, and sometimes even…

Replication of SARS-CoV2 virions is an error-prone process which may eventually generate a percentage of impaired protein copies with complete lack of functionality. For instance, after RNA mis-replication, a very premature stop codon (UAG,…

The identification of the transmission parameters of a virus is fundamental to identify the optimal public health strategy. These parameters can present significant changes over time caused by genetic mutations or viral recombination,…

Variational autoencoders (VAEs) are a popular class of deep generative models with many variants and a wide range of applications. Improvements upon the standard VAE mostly focus on the modelling of the posterior distribution over the…

The current pandemic of SARS-CoV-2 has caused extensive damage to society. The characterization of SARS-CoV-2 profiles has been addressed by researchers globally with the aim of resolving this disruptive crisis. This investigation process…

In winter of 2020, SARS-CoV-2 emerged as a global threat, impacting not only health but also financial and political stability. To address the societal need for monitoring the spread of SARS-CoV-2, many existing diagnostic technologies were…