In silico dynamics of COVID-19 phenotypes for optimizing clinical management
임상 관리 최적화를 위한 COVID-19 표현형의 인 실리코 역학
Biological Sciences
[키워드] ACE2
activated
acute respiratory syndrome
acute respiratory syndrome coronavirus
acute respiratory syndrome coronavirus 2
Adaptive immune response
adaptive immune responses
age
Antiviral
baseline
best
CD8
cellular entry
Clinical data
clinical heterogeneity
Clinical management
Clinical outcome
clinical outcomes
Coagulation
coagulation cascade
Combination
Comorbidities
Comorbidity
coronavirus
COVID-19
COVID-19 patients
COVID-19 phenotype
COVID-19 progression
Cytokines
diabetes
Disease progression
distinctive feature
dysregulated immune response
element
elements
Evolution
extreme
Factors
framework
Health status
healthy
heterogeneity
hypertension
identify
immune
immune cells
immune responses
Infection
Inflammatory cytokines
innate immune response
life
life threatening
management
mathematical
mathematical model
mechanism
Model
modulating
obesity
Older
Older age
outcome
oxygen
oxygen saturation
Patient
pharmaceutical intervention
predict
presence of comorbidities
protocols
provide
Renin
response rate
reveal
risk factor
SARS-CoV-2
SARS-CoV-2 pathogenesis
severe acute respiratory syndrome Coronavirus
Significance
Simulation
sustained
symptomatic
T cell
T cells
the disease
the patient
therapeutic
Therapies
thrombosis
Thrombus
thrombus formation
Trajectories
Treatment
Treatment response
understanding
Viral
viral dynamics
Viral load
viral replication
virus
were used
[DOI] 10.1073/pnas.2021642118 PMC 바로가기 [Article Type] Biological Sciences
[DOI] 10.1073/pnas.2021642118 PMC 바로가기 [Article Type] Biological Sciences