{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T02:09:43Z","timestamp":1772503783569,"version":"3.50.1"},"reference-count":51,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T00:00:00Z","timestamp":1605484800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["#1943777"],"award-info":[{"award-number":["#1943777"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,16]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>The cGAS pathway is a component of the innate immune system responsible for the detection of pathogenic DNA and upregulation of interferon beta (IFN\u03b2). Experimental evidence shows that IFN\u03b2 signaling occurs in highly heterogeneous cells and is stochastic in nature; however, the benefits of these attributes remain unclear. To investigate how stochasticity and heterogeneity affect IFN\u03b2 production, an agent-based model is developed to simulate both DNA transfection and viral infection.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We show that heterogeneity can enhance IFN\u03b2 responses during infection. Furthermore, by varying the degree of IFN\u03b2 stochasticity, we find that only a percentage of cells (20\u201330%) need to respond during infection. Going beyond this range provides no additional protection against cell death or reduction of viral load. Overall, these simulations suggest that heterogeneity and stochasticity are important for moderating immune potency while minimizing cell death during infection.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Model repository is available at: https:\/\/github.com\/ImmuSystems-Lab\/AgentBasedModel-cGASPathway.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa969","type":"journal-article","created":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T04:15:35Z","timestamp":1604549735000},"page":"1428-1434","source":"Crossref","is-referenced-by-count":19,"title":["Agent-based modeling reveals benefits of heterogeneous and stochastic cell populations during cGAS-mediated IFN\u03b2 production"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2930-621X","authenticated-orcid":false,"given":"Robert W","family":"Gregg","sequence":"first","affiliation":[{"name":"Department of Chemical and Petroleum Engineering, 15260 , Pittsburgh, PA 15260, USA"}]},{"given":"Fathima","family":"Shabnam","sequence":"additional","affiliation":[{"name":"Department of Chemical and Petroleum Engineering, 15260 , Pittsburgh, PA 15260, USA"}]},{"given":"Jason E","family":"Shoemaker","sequence":"additional","affiliation":[{"name":"Department of Chemical and Petroleum Engineering, 15260 , Pittsburgh, PA 15260, USA"},{"name":"McGowan Institute for Regenerative Medicine, 15219 , Pittsburgh, PA 15260, USA"},{"name":"Department of Computational and Systems Biology, University of Pittsburgh , Pittsburgh, PA 15260, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,12,10]]},"reference":[{"key":"2023051800333590000_btaa969-B1","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1186\/s12918-017-0406-4","article-title":"A new efficient approach to fit stochastic models on the basis of high-throughput experimental data using a model of IRF7 gene expression as case study","volume":"11","author":"Aguilera","year":"2017","journal-title":"BMC Syst. 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