Validated models of immune response to virus infection

Research output: Contribution to journalReview article

1 Citation (Scopus)

Abstract

Viruses are a main cause of disease worldwide and many are without effective therapeutics or vaccines. A lack of understanding about how host responses work to control viral spread is one factor limiting effective management. How different immune components regulate infection dynamics is beginning to be better understood with the help of mathematical models. These models have been key in discriminating between hypotheses and in identifying rates of virus growth and clearance, dynamical control by different host factors and antivirals, and synergistic interactions during multi-pathogen infections. A recent focus in evaluating model predictions in the laboratory and clinic has illuminate the accuracy of models for a variety of viruses and highlighted the critical nature of theoretical approaches in virology. Here, I discuss recent model-driven exploration of host-pathogen interactions that have illustrated the importance of model validation in establishing the model's predictive capability and in defining new biology.

Original languageEnglish (US)
Pages (from-to)46-52
Number of pages7
JournalCurrent Opinion in Systems Biology
Volume12
DOIs
StatePublished - Dec 1 2018

Fingerprint

Immune Response
Virus Diseases
Viruses
Virus
Infection
Host-Pathogen Interactions
Virology
Pathogens
Antiviral Agents
Model Validation
Vaccine
Theoretical Models
Vaccines
Clearance
Interaction
Model
Prediction Model
Biology
Limiting
Mathematical Model

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

Cite this

Validated models of immune response to virus infection. / Smith, Amber.

In: Current Opinion in Systems Biology, Vol. 12, 01.12.2018, p. 46-52.

Research output: Contribution to journalReview article

@article{463f5ea5a4ef48dd95b41dfb5667b532,
title = "Validated models of immune response to virus infection",
abstract = "Viruses are a main cause of disease worldwide and many are without effective therapeutics or vaccines. A lack of understanding about how host responses work to control viral spread is one factor limiting effective management. How different immune components regulate infection dynamics is beginning to be better understood with the help of mathematical models. These models have been key in discriminating between hypotheses and in identifying rates of virus growth and clearance, dynamical control by different host factors and antivirals, and synergistic interactions during multi-pathogen infections. A recent focus in evaluating model predictions in the laboratory and clinic has illuminate the accuracy of models for a variety of viruses and highlighted the critical nature of theoretical approaches in virology. Here, I discuss recent model-driven exploration of host-pathogen interactions that have illustrated the importance of model validation in establishing the model's predictive capability and in defining new biology.",
author = "Amber Smith",
year = "2018",
month = "12",
day = "1",
doi = "10.1016/j.coisb.2018.10.005",
language = "English (US)",
volume = "12",
pages = "46--52",
journal = "Current Opinion in Systems Biology",
issn = "2452-3100",
publisher = "Elsevier Ltd",

}

TY - JOUR

T1 - Validated models of immune response to virus infection

AU - Smith, Amber

PY - 2018/12/1

Y1 - 2018/12/1

N2 - Viruses are a main cause of disease worldwide and many are without effective therapeutics or vaccines. A lack of understanding about how host responses work to control viral spread is one factor limiting effective management. How different immune components regulate infection dynamics is beginning to be better understood with the help of mathematical models. These models have been key in discriminating between hypotheses and in identifying rates of virus growth and clearance, dynamical control by different host factors and antivirals, and synergistic interactions during multi-pathogen infections. A recent focus in evaluating model predictions in the laboratory and clinic has illuminate the accuracy of models for a variety of viruses and highlighted the critical nature of theoretical approaches in virology. Here, I discuss recent model-driven exploration of host-pathogen interactions that have illustrated the importance of model validation in establishing the model's predictive capability and in defining new biology.

AB - Viruses are a main cause of disease worldwide and many are without effective therapeutics or vaccines. A lack of understanding about how host responses work to control viral spread is one factor limiting effective management. How different immune components regulate infection dynamics is beginning to be better understood with the help of mathematical models. These models have been key in discriminating between hypotheses and in identifying rates of virus growth and clearance, dynamical control by different host factors and antivirals, and synergistic interactions during multi-pathogen infections. A recent focus in evaluating model predictions in the laboratory and clinic has illuminate the accuracy of models for a variety of viruses and highlighted the critical nature of theoretical approaches in virology. Here, I discuss recent model-driven exploration of host-pathogen interactions that have illustrated the importance of model validation in establishing the model's predictive capability and in defining new biology.

UR - http://www.scopus.com/inward/record.url?scp=85056572531&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056572531&partnerID=8YFLogxK

U2 - 10.1016/j.coisb.2018.10.005

DO - 10.1016/j.coisb.2018.10.005

M3 - Review article

VL - 12

SP - 46

EP - 52

JO - Current Opinion in Systems Biology

JF - Current Opinion in Systems Biology

SN - 2452-3100

ER -