2022
DOI: 10.1002/cbf.3769
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Molecular modeling of C1‐inhibitor as SARS‐CoV‐2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study

Abstract: The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength and caused a veritable collapse in health infrastructure. The molecular modeling of the novel coronavirus research sounds promising and equips more evidence about the pragmatic therapeutic options. This article proposes a machine-learning framework for identifying potential COVID-19 transcriptomic signatures. The transcriptomics data contains immune-related genes … Show more

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Cited by 2 publications
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“…Although ML approaches help to identify putative biomarkers, their potentiality must be assessed by highly developed computational techniques. In addition, greater model complexity is typically used to attain higher performance, turning these systems into blackbox methods that create ambiguity in their functionality and decision-making ability [24][25][26]. Relying on models whose findings cannot be comprehended efficiently is quite laborious.…”
Section: Introductionmentioning
confidence: 99%
“…Although ML approaches help to identify putative biomarkers, their potentiality must be assessed by highly developed computational techniques. In addition, greater model complexity is typically used to attain higher performance, turning these systems into blackbox methods that create ambiguity in their functionality and decision-making ability [24][25][26]. Relying on models whose findings cannot be comprehended efficiently is quite laborious.…”
Section: Introductionmentioning
confidence: 99%