schliessen

Filtern

 

Bibliotheken

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, whic... Full description

Journal Title: PLoS ONE 01 January 2015, Vol.10(9), p.e0136139
Main Author: Maksudul Alam
Other Authors: Xinwei Deng , Casandra Philipson , Josep Bassaganya-Riera , Keith Bisset , Adria Carbo , Stephen Eubank , Raquel Hontecillas , Stefan Hoops , Yongguo Mei , Vida Abedi , Madhav Marathe
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: E-ISSN: 1932-6203 ; DOI: 10.1371/journal.pone.0136139
Zum Text:
SendSend as email Add to Book BagAdd to Book Bag
Staff View
recordid: doaj_soai_doaj_org_article_f6e1c2bc8d59456aa2eab0d2117f43e8
title: Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection
format: Article
creator:
  • Maksudul Alam
  • Xinwei Deng
  • Casandra Philipson
  • Josep Bassaganya-Riera
  • Keith Bisset
  • Adria Carbo
  • Stephen Eubank
  • Raquel Hontecillas
  • Stefan Hoops
  • Yongguo Mei
  • Vida Abedi
  • Madhav Marathe
subjects:
  • Sciences (General)
ispartof: PLoS ONE, 01 January 2015, Vol.10(9), p.e0136139
description: Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.
language: eng
source:
identifier: E-ISSN: 1932-6203 ; DOI: 10.1371/journal.pone.0136139
fulltext: fulltext_linktorsrc
issn:
  • 1932-6203
  • 19326203
url: Link


@attributes
ID513545780
RANK0.07
NO1
SEARCH_ENGINEprimo_central_multiple_fe
SEARCH_ENGINE_TYPEPrimo Central Search Engine
LOCALfalse
PrimoNMBib
record
control
sourcerecordidoai_doaj_org_article_f6e1c2bc8d59456aa2eab0d2117f43e8
sourceiddoaj_s
recordidTN_doaj_soai_doaj_org_article_f6e1c2bc8d59456aa2eab0d2117f43e8
sourcesystemPC
dbidDOA
pqid1709394860
galeid427623002
display
typearticle
titleSensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection
creatorMaksudul Alam ; Xinwei Deng ; Casandra Philipson ; Josep Bassaganya-Riera ; Keith Bisset ; Adria Carbo ; Stephen Eubank ; Raquel Hontecillas ; Stefan Hoops ; Yongguo Mei ; Vida Abedi ; Madhav Marathe
ispartofPLoS ONE, 01 January 2015, Vol.10(9), p.e0136139
identifierE-ISSN: 1932-6203 ; DOI: 10.1371/journal.pone.0136139
subjectSciences (General)
languageeng
oafree_for_read
source
descriptionAgent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.
version9
lds50peer_reviewed
links
openurl$$Topenurl_article
openurlfulltext$$Topenurlfull_article
linktorsrc$$Uhttps://doaj.org/article/f6e1c2bc8d59456aa2eab0d2117f43e8$$EView_full_text_in_DOAJ
search
creatorcontrib
0Maksudul Alam
1Xinwei Deng
2Casandra Philipson
3Josep Bassaganya-Riera
4Keith Bisset
5Adria Carbo
6Stephen Eubank
7Raquel Hontecillas
8Stefan Hoops
9Yongguo Mei
10Vida Abedi
11Madhav Marathe
titleSensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection
description

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings....

subjectSciences (General)
general
0English
1Public Library of Science (PLoS)
210.1371/journal.pone.0136139
3Directory of Open Access Journals (DOAJ)
sourceiddoaj_s
recordiddoaj_soai_doaj_org_article_f6e1c2bc8d59456aa2eab0d2117f43e8
issn
01932-6203
119326203
rsrctypearticle
creationdate2015
addtitlePLoS ONE
searchscope
0doaj_full
1doaj1
scope
0doaj_full
1doaj1
lsr45$$EView_full_text_in_DOAJ
tmp01Directory of Open Access Journals (DOAJ)
tmp02DOA
startdate20150101
enddate20150101
lsr40PLoS ONE, 01 January 2015, Vol.10 (9), p.e0136139
doi10.1371/journal.pone.0136139
citationpf e0136139 vol 10 issue 9
lsr30VSR-Enriched:[date, galeid, pages, pqid, description]
sort
titleSensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection
authorMaksudul Alam ; Xinwei Deng ; Casandra Philipson ; Josep Bassaganya-Riera ; Keith Bisset ; Adria Carbo ; Stephen Eubank ; Raquel Hontecillas ; Stefan Hoops ; Yongguo Mei ; Vida Abedi ; Madhav Marathe
creationdate20150101
lso0120150101
facets
frbrgroupid8484377488233194701
frbrtype5
newrecords20200226
languageeng
topicSciences (General)
collectionDirectory of Open Access Journals (DOAJ)
prefilterarticles
rsrctypearticles
creatorcontrib
0Maksudul Alam
1Xinwei Deng
2Casandra Philipson
3Josep Bassaganya-Riera
4Keith Bisset
5Adria Carbo
6Stephen Eubank
7Raquel Hontecillas
8Stefan Hoops
9Yongguo Mei
10Vida Abedi
11Madhav Marathe
jtitlePLoS ONE
creationdate2015
toplevelpeer_reviewed
delivery
delcategoryRemote Search Resource
fulltextfulltext_linktorsrc
addata
au
0Maksudul Alam
1Xinwei Deng
2Casandra Philipson
3Josep Bassaganya-Riera
4Keith Bisset
5Adria Carbo
6Stephen Eubank
7Raquel Hontecillas
8Stefan Hoops
9Yongguo Mei
10Vida Abedi
11Madhav Marathe
atitleSensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection
jtitlePLoS ONE
risdate20150101
volume10
issue9
spagee0136139
eissn1932-6203
formatjournal
genrearticle
ristypeJOUR
abstract

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings....

pubPublic Library of Science (PLoS)
doi10.1371/journal.pone.0136139
urlhttps://doaj.org/article/f6e1c2bc8d59456aa2eab0d2117f43e8
lad01PLoS ONE
oafree_for_read
pagese0136139
date2015-09-01