A Greedy Heuristic for Cluster Editing with Vertex Splitting

Abu-Khzam, Faisal N.; Barr, Joseph R.; Fakhereldine, Amin; Shaw, Peter

doi:10.1109/ai4i51902.2021.00017

Cited by 7 publications

(1 citation statement)

References 18 publications

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“…Lastly, having all of this big data will allow researchers to use Machine Learning (ML) and various novel network search algorithms [61,62] to predict the effect of future SARS-CoV* strains in a particular region or a geographical location based on their biological and immunological capabilities and not just the genetic backbone, which will give the scientific and medical communities a considerable advantage in refocusing their limited resources.…”

Section: (6)mentioning

confidence: 99%

COVID-19: The Ethno-Geographic Perspective of Differential Immunity

Abdullah¹,

Saleh²,

Shaw³

et al. 2022

Preprint

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Coronavirus disease 2019 (COVID-19), the emissary behind the worst global pandemic of the 21st century, is primarily a respiratory disease-causing virus called SARS-CoV-2 which is responsible for millions of new cases (incidence) and deaths (mortalities), worldwide. Many factors have played a role in the differential morbidity and mortality experienced by nations and ethnicities against SARS-CoV-2, such as the quality of primary medical health facilities or enabling economies. Nevertheless, the most important variable, i.e., the subsequent ability of individuals to be immunologically sensitive or resistant to the infection, was not properly discussed before. Therefore, an astounding issue arose when some developed countries experienced higher morbidity and mortality, compared with their relatively underdeveloped counterparts, despite having excellent medical health facilities. Hence this investigative review attempts to analyze the issue from an angle of previously undiscussed genetic, epigenetic, and molecular immune resistance mechanisms in correlation with the pathophysiology of SARS-CoV-2 and varied ethnicity-based immunological responses against it. The biological factors discussed here include the overall landscape of human microbiota, endogenous retroviral genes spliced into the human genome, copy number variation, and how they could modulate the innate and adaptive immune systems, which put a particular ethnic genetic architecture at a higher risk of SARS-CoV-2 infection than others. Considering an array of these factors in their entirety may help explain the geographic disparity of disease incidence, severity, and subsequent mortality associated with the disease while at the same time encouraging scientists to design new experimental approaches to investigation.

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Section: (6)mentioning

confidence: 99%