Mathematical models to study the biology of pathogens and the infectious diseases they cause.

Autor:	Xavier JB; Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA., Monk JM; Department of Bioengineering, UC San Diego, San Diego, CA, USA., Poudel S; Department of Bioengineering, UC San Diego, San Diego, CA, USA., Norsigian CJ; Department of Bioengineering, UC San Diego, San Diego, CA, USA., Sastry AV; Department of Bioengineering, UC San Diego, San Diego, CA, USA., Liao C; Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA., Bento J; Computer Science Department, Boston College, Chestnut Hill, MA, USA., Suchard MA; Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA., Arrieta-Ortiz ML; Institute for Systems Biology, Seattle, WA, USA., Peterson EJR; Institute for Systems Biology, Seattle, WA, USA., Baliga NS; Institute for Systems Biology, Seattle, WA, USA., Stoeger T; Department of Chemical and Biological Engineering; Northwestern University, Evanston, IL 60208, USA.; Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, Chicago, IL, USA., Ruffin F; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA., Richardson RAK; Department of Chemical and Biological Engineering; Northwestern University, Evanston, IL 60208, USA.; Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, Chicago, IL, USA., Gao CA; Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, Chicago, IL, USA.; Division of Pulmonary and Critical Care, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA., Horvath TD; Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA.; Department of Pathology, Texas Children's Microbiome Center, Texas Children's Hospital, Houston, TX 77030, USA., Haag AM; Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA.; Department of Pathology, Texas Children's Microbiome Center, Texas Children's Hospital, Houston, TX 77030, USA., Wu Q; Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA.; Department of Pathology, Texas Children's Microbiome Center, Texas Children's Hospital, Houston, TX 77030, USA., Savidge T; Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA.; Department of Pathology, Texas Children's Microbiome Center, Texas Children's Hospital, Houston, TX 77030, USA., Yeaman MR; David Geffen School of Medicine at UCLA & Lundquist Institute for Infection & Immunity at Harbor UCLA Medical Center, Los Angeles, CA, USA.
Jazyk:	angličtina
Zdroj:	IScience [iScience] 2022 Mar 15; Vol. 25 (4), pp. 104079. Date of Electronic Publication: 2022 Mar 15 (Print Publication: 2022).
DOI:	10.1016/j.isci.2022.104079
Abstrakt:	Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause. (© 2022 The Author(s).)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu