Analytical results on the Beauchemin model of lymphocyte migration View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2013-04-17

AUTHORS

Johannes Textor, Mathieu Sinn, Rob J de Boer

ABSTRACT

The Beauchemin model is a simple particle-based description of stochastic lymphocyte migration in tissue, which has been successfully applied to studying immunological questions. In addition to being easy to implement, the model is also to a large extent mathematically tractable. This article provides a comprehensive overview of both existing and new analytical results on the Beauchemin model within a common mathematical framework. Specifically, we derive the motility coefficient, the mean square displacement, and the confinement ratio, and discuss four different methods for simulating biased migration of pre-defined speed. The results provide new insight into published studies and a reference point for future research based on this simple and popular lymphocyte migration model. More... »

PAGES

s10

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2105-14-s6-s10

DOI

http://dx.doi.org/10.1186/1471-2105-14-s6-s10

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034767811

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23734948


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cell Movement", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chemotaxis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Lymphocytes", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Biological", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institute for Theoretical Computer Science, University of L\u00fcbeck, 23562, L\u00fcbeck, Germany", 
          "id": "http://www.grid.ac/institutes/grid.4562.5", 
          "name": [
            "Theoretical Biology & Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands", 
            "Institute for Theoretical Computer Science, University of L\u00fcbeck, 23562, L\u00fcbeck, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Textor", 
        "givenName": "Johannes", 
        "id": "sg:person.01227556406.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01227556406.26"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "IBM Research, Mulhuddart, Dublin 15, Ireland", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "IBM Research, Mulhuddart, Dublin 15, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sinn", 
        "givenName": "Mathieu", 
        "id": "sg:person.014605174645.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014605174645.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Theoretical Biology & Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands", 
          "id": "http://www.grid.ac/institutes/grid.5477.1", 
          "name": [
            "Theoretical Biology & Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "de Boer", 
        "givenName": "Rob J", 
        "id": "sg:person.0774503452.97", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774503452.97"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/nri2638", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008648027", 
          "https://doi.org/10.1038/nri2638"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-4015-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109705758", 
          "https://doi.org/10.1007/978-1-4757-4015-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00249-004-0426-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046054538", 
          "https://doi.org/10.1007/s00249-004-0426-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/b98868", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028080802", 
          "https://doi.org/10.1007/b98868"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature02238", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007518600", 
          "https://doi.org/10.1038/nature02238"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04651", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024462310", 
          "https://doi.org/10.1038/nature04651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00285-003-0220-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050057588", 
          "https://doi.org/10.1007/s00285-003-0220-z"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-04-17", 
    "datePublishedReg": "2013-04-17", 
    "description": "The Beauchemin model is a simple particle-based description of stochastic lymphocyte migration in tissue, which has been successfully applied to studying immunological questions. In addition to being easy to implement, the model is also to a large extent mathematically tractable. This article provides a comprehensive overview of both existing and new analytical results on the Beauchemin model within a common mathematical framework. Specifically, we derive the motility coefficient, the mean square displacement, and the confinement ratio, and discuss four different methods for simulating biased migration of pre-defined speed. The results provide new insight into published studies and a reference point for future research based on this simple and popular lymphocyte migration model.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/1471-2105-14-s6-s10", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1023786", 
        "issn": [
          "1471-2105"
        ], 
        "name": "BMC Bioinformatics", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "Suppl 6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "14"
      }
    ], 
    "keywords": [
      "common mathematical framework", 
      "analytical results", 
      "new analytical results", 
      "mathematical framework", 
      "mean square displacement", 
      "particle-based description", 
      "pre-defined speed", 
      "motility coefficient", 
      "square displacement", 
      "biased migration", 
      "migration model", 
      "model", 
      "different methods", 
      "reference point", 
      "confinement ratio", 
      "description", 
      "immunological questions", 
      "coefficient", 
      "results", 
      "speed", 
      "point", 
      "framework", 
      "displacement", 
      "large extent", 
      "ratio", 
      "new insights", 
      "article", 
      "comprehensive overview", 
      "overview", 
      "questions", 
      "insights", 
      "addition", 
      "research", 
      "study", 
      "migration", 
      "extent", 
      "future research", 
      "lymphocyte migration", 
      "tissue", 
      "method"
    ], 
    "name": "Analytical results on the Beauchemin model of lymphocyte migration", 
    "pagination": "s10", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1034767811"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2105-14-s6-s10"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "23734948"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2105-14-s6-s10", 
      "https://app.dimensions.ai/details/publication/pub.1034767811"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-09-02T15:57", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_603.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/1471-2105-14-s6-s10"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-14-s6-s10'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-14-s6-s10'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-14-s6-s10'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-14-s6-s10'


 

This table displays all metadata directly associated to this object as RDF triples.

169 TRIPLES      21 PREDICATES      76 URIs      61 LITERALS      12 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2105-14-s6-s10 schema:about N0c6e3112f1d244018d77da7fe69db57e
2 N10f8452cd6964169b1e8a15b51f6af05
3 Nb7df446becea42caad86ff373f62839d
4 Nf0dc29ad181a49a4ac6d3e1e1cfef2f0
5 Nfaba56e16dca40f289d565c6880f1b19
6 anzsrc-for:01
7 anzsrc-for:0104
8 schema:author Na8ea6b769faf470f9590e367e59706fe
9 schema:citation sg:pub.10.1007/978-1-4757-4015-8
10 sg:pub.10.1007/b98868
11 sg:pub.10.1007/s00249-004-0426-z
12 sg:pub.10.1007/s00285-003-0220-z
13 sg:pub.10.1038/nature02238
14 sg:pub.10.1038/nature04651
15 sg:pub.10.1038/nri2638
16 schema:datePublished 2013-04-17
17 schema:datePublishedReg 2013-04-17
18 schema:description The Beauchemin model is a simple particle-based description of stochastic lymphocyte migration in tissue, which has been successfully applied to studying immunological questions. In addition to being easy to implement, the model is also to a large extent mathematically tractable. This article provides a comprehensive overview of both existing and new analytical results on the Beauchemin model within a common mathematical framework. Specifically, we derive the motility coefficient, the mean square displacement, and the confinement ratio, and discuss four different methods for simulating biased migration of pre-defined speed. The results provide new insight into published studies and a reference point for future research based on this simple and popular lymphocyte migration model.
19 schema:genre article
20 schema:isAccessibleForFree true
21 schema:isPartOf N4612899991ef44e8a4eb9fb4a8a49711
22 N89bcf3d692d548bba63621592d302e1d
23 sg:journal.1023786
24 schema:keywords addition
25 analytical results
26 article
27 biased migration
28 coefficient
29 common mathematical framework
30 comprehensive overview
31 confinement ratio
32 description
33 different methods
34 displacement
35 extent
36 framework
37 future research
38 immunological questions
39 insights
40 large extent
41 lymphocyte migration
42 mathematical framework
43 mean square displacement
44 method
45 migration
46 migration model
47 model
48 motility coefficient
49 new analytical results
50 new insights
51 overview
52 particle-based description
53 point
54 pre-defined speed
55 questions
56 ratio
57 reference point
58 research
59 results
60 speed
61 square displacement
62 study
63 tissue
64 schema:name Analytical results on the Beauchemin model of lymphocyte migration
65 schema:pagination s10
66 schema:productId N33ab0683158c464794c07777037fadc1
67 Nd06bfa65326b46c79180a982b5acc4d0
68 Nf9d6b024ff90437981f8ce3e564aa448
69 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034767811
70 https://doi.org/10.1186/1471-2105-14-s6-s10
71 schema:sdDatePublished 2022-09-02T15:57
72 schema:sdLicense https://scigraph.springernature.com/explorer/license/
73 schema:sdPublisher Nfe9b14007f2b474b9298193287e3bd49
74 schema:url https://doi.org/10.1186/1471-2105-14-s6-s10
75 sgo:license sg:explorer/license/
76 sgo:sdDataset articles
77 rdf:type schema:ScholarlyArticle
78 N0c6e3112f1d244018d77da7fe69db57e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
79 schema:name Cell Movement
80 rdf:type schema:DefinedTerm
81 N10f8452cd6964169b1e8a15b51f6af05 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
82 schema:name Chemotaxis
83 rdf:type schema:DefinedTerm
84 N1c29cec13f6d4dfeb9d80998eaadf736 rdf:first sg:person.014605174645.48
85 rdf:rest Na589f25d75534fda9f86133c8ff3c6a6
86 N33ab0683158c464794c07777037fadc1 schema:name dimensions_id
87 schema:value pub.1034767811
88 rdf:type schema:PropertyValue
89 N4612899991ef44e8a4eb9fb4a8a49711 schema:issueNumber Suppl 6
90 rdf:type schema:PublicationIssue
91 N89bcf3d692d548bba63621592d302e1d schema:volumeNumber 14
92 rdf:type schema:PublicationVolume
93 Na589f25d75534fda9f86133c8ff3c6a6 rdf:first sg:person.0774503452.97
94 rdf:rest rdf:nil
95 Na8ea6b769faf470f9590e367e59706fe rdf:first sg:person.01227556406.26
96 rdf:rest N1c29cec13f6d4dfeb9d80998eaadf736
97 Nb7df446becea42caad86ff373f62839d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Lymphocytes
99 rdf:type schema:DefinedTerm
100 Nd06bfa65326b46c79180a982b5acc4d0 schema:name pubmed_id
101 schema:value 23734948
102 rdf:type schema:PropertyValue
103 Nf0dc29ad181a49a4ac6d3e1e1cfef2f0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Models, Biological
105 rdf:type schema:DefinedTerm
106 Nf9d6b024ff90437981f8ce3e564aa448 schema:name doi
107 schema:value 10.1186/1471-2105-14-s6-s10
108 rdf:type schema:PropertyValue
109 Nfaba56e16dca40f289d565c6880f1b19 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
110 schema:name Animals
111 rdf:type schema:DefinedTerm
112 Nfe9b14007f2b474b9298193287e3bd49 schema:name Springer Nature - SN SciGraph project
113 rdf:type schema:Organization
114 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
115 schema:name Mathematical Sciences
116 rdf:type schema:DefinedTerm
117 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
118 schema:name Statistics
119 rdf:type schema:DefinedTerm
120 sg:journal.1023786 schema:issn 1471-2105
121 schema:name BMC Bioinformatics
122 schema:publisher Springer Nature
123 rdf:type schema:Periodical
124 sg:person.01227556406.26 schema:affiliation grid-institutes:grid.4562.5
125 schema:familyName Textor
126 schema:givenName Johannes
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01227556406.26
128 rdf:type schema:Person
129 sg:person.014605174645.48 schema:affiliation grid-institutes:None
130 schema:familyName Sinn
131 schema:givenName Mathieu
132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014605174645.48
133 rdf:type schema:Person
134 sg:person.0774503452.97 schema:affiliation grid-institutes:grid.5477.1
135 schema:familyName de Boer
136 schema:givenName Rob J
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774503452.97
138 rdf:type schema:Person
139 sg:pub.10.1007/978-1-4757-4015-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109705758
140 https://doi.org/10.1007/978-1-4757-4015-8
141 rdf:type schema:CreativeWork
142 sg:pub.10.1007/b98868 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028080802
143 https://doi.org/10.1007/b98868
144 rdf:type schema:CreativeWork
145 sg:pub.10.1007/s00249-004-0426-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1046054538
146 https://doi.org/10.1007/s00249-004-0426-z
147 rdf:type schema:CreativeWork
148 sg:pub.10.1007/s00285-003-0220-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1050057588
149 https://doi.org/10.1007/s00285-003-0220-z
150 rdf:type schema:CreativeWork
151 sg:pub.10.1038/nature02238 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007518600
152 https://doi.org/10.1038/nature02238
153 rdf:type schema:CreativeWork
154 sg:pub.10.1038/nature04651 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024462310
155 https://doi.org/10.1038/nature04651
156 rdf:type schema:CreativeWork
157 sg:pub.10.1038/nri2638 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008648027
158 https://doi.org/10.1038/nri2638
159 rdf:type schema:CreativeWork
160 grid-institutes:None schema:alternateName IBM Research, Mulhuddart, Dublin 15, Ireland
161 schema:name IBM Research, Mulhuddart, Dublin 15, Ireland
162 rdf:type schema:Organization
163 grid-institutes:grid.4562.5 schema:alternateName Institute for Theoretical Computer Science, University of Lübeck, 23562, Lübeck, Germany
164 schema:name Institute for Theoretical Computer Science, University of Lübeck, 23562, Lübeck, Germany
165 Theoretical Biology & Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands
166 rdf:type schema:Organization
167 grid-institutes:grid.5477.1 schema:alternateName Theoretical Biology & Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands
168 schema:name Theoretical Biology & Bioinformatics, Utrecht University, 3508 TC Utrecht, The Netherlands
169 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...