A multiscale mathematical model of cancer, and its use in analyzing irradiation therapies View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2006-02-10

AUTHORS

Benjamin Ribba, Thierry Colin, Santiago Schnell

ABSTRACT

BACKGROUND: Radiotherapy outcomes are usually predicted using the Linear Quadratic model. However, this model does not integrate complex features of tumor growth, in particular cell cycle regulation. METHODS: In this paper, we propose a multiscale model of cancer growth based on the genetic and molecular features of the evolution of colorectal cancer. The model includes key genes, cellular kinetics, tissue dynamics, macroscopic tumor evolution and radiosensitivity dependence on the cell cycle phase. We investigate the role of gene-dependent cell cycle regulation in the response of tumors to therapeutic irradiation protocols. RESULTS: Simulation results emphasize the importance of tumor tissue features and the need to consider regulating factors such as hypoxia, as well as tumor geometry and tissue dynamics, in predicting and improving radiotherapeutic efficacy. CONCLUSION: This model provides insight into the coupling of complex biological processes, which leads to a better understanding of oncogenesis. This will hopefully lead to improved irradiation therapy. More... »

PAGES

7-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1742-4682-3-7

DOI

http://dx.doi.org/10.1186/1742-4682-3-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049887481

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16472396


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/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cell Cycle", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Dose-Response Relationship, Radiation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Biological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Software", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Institute for Theoretical Medicine and Clinical Pharmacology Department, Faculty of Medicine R.T.H Laennec, University of Lyon, Paradin St., P.O.B 8071, 69376 Lyon Cedex 08, France", 
          "id": "http://www.grid.ac/institutes/grid.25697.3f", 
          "name": [
            "Institute for Theoretical Medicine and Clinical Pharmacology Department, Faculty of Medicine R.T.H Laennec, University of Lyon, Paradin St., P.O.B 8071, 69376 Lyon Cedex 08, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ribba", 
        "givenName": "Benjamin", 
        "id": "sg:person.0751077254.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0751077254.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Math\u00e9matiques Appliqu\u00e9es de Bordeaux, CNRS UMR 5466 and INRIA futurs, University of Bordeaux 1, 351 cours de la liberation, 33405 Talence Cedex, France", 
          "id": "http://www.grid.ac/institutes/grid.412041.2", 
          "name": [
            "Math\u00e9matiques Appliqu\u00e9es de Bordeaux, CNRS UMR 5466 and INRIA futurs, University of Bordeaux 1, 351 cours de la liberation, 33405 Talence Cedex, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Colin", 
        "givenName": "Thierry", 
        "id": "sg:person.01350720433.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350720433.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Indiana University School of Informatics and Biocomplexity Institute, 1900 East Tenth Street, Eigenmann Hall 906, Bloomington, IN 47406, USA", 
          "id": "http://www.grid.ac/institutes/grid.411377.7", 
          "name": [
            "Indiana University School of Informatics and Biocomplexity Institute, 1900 East Tenth Street, Eigenmann Hall 906, Bloomington, IN 47406, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schnell", 
        "givenName": "Santiago", 
        "id": "sg:person.01056742320.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01056742320.15"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/273345a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024073968", 
          "https://doi.org/10.1038/273345a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.bjc.6602622", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011707440", 
          "https://doi.org/10.1038/sj.bjc.6602622"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.onc.1208615", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039884704", 
          "https://doi.org/10.1038/sj.onc.1208615"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1006/bulm.1998.0042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019334301", 
          "https://doi.org/10.1006/bulm.1998.0042"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/352345a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007959161", 
          "https://doi.org/10.1038/352345a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/29343", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016163271", 
          "https://doi.org/10.1038/29343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrc795", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045099768", 
          "https://doi.org/10.1038/nrc795"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1016/j.bulm.2004.06.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029788365", 
          "https://doi.org/10.1016/j.bulm.2004.06.007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1006/bulm.2000.0217", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051771928", 
          "https://doi.org/10.1006/bulm.2000.0217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/bjc.1998.503", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031456244", 
          "https://doi.org/10.1038/bjc.1998.503"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2006-02-10", 
    "datePublishedReg": "2006-02-10", 
    "description": "BACKGROUND: Radiotherapy outcomes are usually predicted using the Linear Quadratic model. However, this model does not integrate complex features of tumor growth, in particular cell cycle regulation.\nMETHODS: In this paper, we propose a multiscale model of cancer growth based on the genetic and molecular features of the evolution of colorectal cancer. The model includes key genes, cellular kinetics, tissue dynamics, macroscopic tumor evolution and radiosensitivity dependence on the cell cycle phase. We investigate the role of gene-dependent cell cycle regulation in the response of tumors to therapeutic irradiation protocols.\nRESULTS: Simulation results emphasize the importance of tumor tissue features and the need to consider regulating factors such as hypoxia, as well as tumor geometry and tissue dynamics, in predicting and improving radiotherapeutic efficacy.\nCONCLUSION: This model provides insight into the coupling of complex biological processes, which leads to a better understanding of oncogenesis. This will hopefully lead to improved irradiation therapy.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/1742-4682-3-7", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2586430", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.3058693", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1034054", 
        "issn": [
          "1742-4682"
        ], 
        "name": "Theoretical Biology and Medical Modelling", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "3"
      }
    ], 
    "keywords": [
      "irradiation therapy", 
      "response of tumors", 
      "colorectal cancer", 
      "linear quadratic model", 
      "tumor growth", 
      "cancer growth", 
      "radiotherapy outcome", 
      "cell cycle regulation", 
      "radiotherapeutic efficacy", 
      "cellular kinetics", 
      "therapy", 
      "cycle regulation", 
      "cancer", 
      "irradiation protocol", 
      "molecular features", 
      "cell cycle phases", 
      "cycle phase", 
      "tumor evolution", 
      "tissue features", 
      "tumors", 
      "hypoxia", 
      "tumor geometry", 
      "efficacy", 
      "outcomes", 
      "multiscale mathematical model", 
      "tissue dynamics", 
      "key genes", 
      "oncogenesis", 
      "regulation", 
      "better understanding", 
      "response", 
      "factors", 
      "features", 
      "role", 
      "protocol", 
      "genes", 
      "complex biological processes", 
      "growth", 
      "use", 
      "need", 
      "biological processes", 
      "model", 
      "importance", 
      "results", 
      "understanding", 
      "insights", 
      "quadratic model", 
      "complex features", 
      "phase", 
      "kinetics", 
      "process", 
      "evolution", 
      "dependence", 
      "mathematical model", 
      "dynamics", 
      "coupling", 
      "multiscale model", 
      "simulation results", 
      "paper", 
      "geometry", 
      "particular cell cycle regulation", 
      "macroscopic tumor evolution", 
      "radiosensitivity dependence", 
      "gene-dependent cell cycle regulation", 
      "therapeutic irradiation protocols", 
      "tumor tissue features", 
      "improved irradiation therapy"
    ], 
    "name": "A multiscale mathematical model of cancer, and its use in analyzing irradiation therapies", 
    "pagination": "7-7", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1049887481"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1742-4682-3-7"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "16472396"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1742-4682-3-7", 
      "https://app.dimensions.ai/details/publication/pub.1049887481"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-12-01T19:18", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/article/article_421.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/1742-4682-3-7"
  }
]
 

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.10.1186/1742-4682-3-7'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1742-4682-3-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1742-4682-3-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1742-4682-3-7'


 

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

208 TRIPLES      22 PREDICATES      107 URIs      90 LITERALS      12 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1742-4682-3-7 schema:about N85f26f8d204d484183fb6424e9b10459
2 N9d8c529a75b14c2c8c0921653dc65170
3 Na4797ff98e70475f9d9dd888ba097e13
4 Nbf17fac6b0bf44b9b0d7b8943fd90aa0
5 Nd4504351317b4876912f16de081ca16f
6 anzsrc-for:06
7 schema:author Nbad9cc6055f34a2386d383d47a22937f
8 schema:citation sg:pub.10.1006/bulm.1998.0042
9 sg:pub.10.1006/bulm.2000.0217
10 sg:pub.10.1016/j.bulm.2004.06.007
11 sg:pub.10.1038/273345a0
12 sg:pub.10.1038/29343
13 sg:pub.10.1038/352345a0
14 sg:pub.10.1038/bjc.1998.503
15 sg:pub.10.1038/nrc795
16 sg:pub.10.1038/sj.bjc.6602622
17 sg:pub.10.1038/sj.onc.1208615
18 schema:datePublished 2006-02-10
19 schema:datePublishedReg 2006-02-10
20 schema:description BACKGROUND: Radiotherapy outcomes are usually predicted using the Linear Quadratic model. However, this model does not integrate complex features of tumor growth, in particular cell cycle regulation. METHODS: In this paper, we propose a multiscale model of cancer growth based on the genetic and molecular features of the evolution of colorectal cancer. The model includes key genes, cellular kinetics, tissue dynamics, macroscopic tumor evolution and radiosensitivity dependence on the cell cycle phase. We investigate the role of gene-dependent cell cycle regulation in the response of tumors to therapeutic irradiation protocols. RESULTS: Simulation results emphasize the importance of tumor tissue features and the need to consider regulating factors such as hypoxia, as well as tumor geometry and tissue dynamics, in predicting and improving radiotherapeutic efficacy. CONCLUSION: This model provides insight into the coupling of complex biological processes, which leads to a better understanding of oncogenesis. This will hopefully lead to improved irradiation therapy.
21 schema:genre article
22 schema:inLanguage en
23 schema:isAccessibleForFree true
24 schema:isPartOf N242023e84834499eb2235bb10e757753
25 Nb1f9270779094a799ec74e072b6b6a31
26 sg:journal.1034054
27 schema:keywords better understanding
28 biological processes
29 cancer
30 cancer growth
31 cell cycle phases
32 cell cycle regulation
33 cellular kinetics
34 colorectal cancer
35 complex biological processes
36 complex features
37 coupling
38 cycle phase
39 cycle regulation
40 dependence
41 dynamics
42 efficacy
43 evolution
44 factors
45 features
46 gene-dependent cell cycle regulation
47 genes
48 geometry
49 growth
50 hypoxia
51 importance
52 improved irradiation therapy
53 insights
54 irradiation protocol
55 irradiation therapy
56 key genes
57 kinetics
58 linear quadratic model
59 macroscopic tumor evolution
60 mathematical model
61 model
62 molecular features
63 multiscale mathematical model
64 multiscale model
65 need
66 oncogenesis
67 outcomes
68 paper
69 particular cell cycle regulation
70 phase
71 process
72 protocol
73 quadratic model
74 radiosensitivity dependence
75 radiotherapeutic efficacy
76 radiotherapy outcome
77 regulation
78 response
79 response of tumors
80 results
81 role
82 simulation results
83 therapeutic irradiation protocols
84 therapy
85 tissue dynamics
86 tissue features
87 tumor evolution
88 tumor geometry
89 tumor growth
90 tumor tissue features
91 tumors
92 understanding
93 use
94 schema:name A multiscale mathematical model of cancer, and its use in analyzing irradiation therapies
95 schema:pagination 7-7
96 schema:productId N5608816b545d43568e712324b9d7400a
97 N6d93bfbd67884f7484937ad0caf3310d
98 Nc83bbdef7e03401394cf82ed52e23ef6
99 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049887481
100 https://doi.org/10.1186/1742-4682-3-7
101 schema:sdDatePublished 2021-12-01T19:18
102 schema:sdLicense https://scigraph.springernature.com/explorer/license/
103 schema:sdPublisher Nc5c8e7639bfc4d5bbf6865a552c439c3
104 schema:url https://doi.org/10.1186/1742-4682-3-7
105 sgo:license sg:explorer/license/
106 sgo:sdDataset articles
107 rdf:type schema:ScholarlyArticle
108 N1bf3e22c8e5246c98b0f53a0b69de14b rdf:first sg:person.01350720433.45
109 rdf:rest N59dd3fc5328e45ab84563c9697aec9c6
110 N242023e84834499eb2235bb10e757753 schema:volumeNumber 3
111 rdf:type schema:PublicationVolume
112 N5608816b545d43568e712324b9d7400a schema:name doi
113 schema:value 10.1186/1742-4682-3-7
114 rdf:type schema:PropertyValue
115 N59dd3fc5328e45ab84563c9697aec9c6 rdf:first sg:person.01056742320.15
116 rdf:rest rdf:nil
117 N6d93bfbd67884f7484937ad0caf3310d schema:name pubmed_id
118 schema:value 16472396
119 rdf:type schema:PropertyValue
120 N85f26f8d204d484183fb6424e9b10459 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Neoplasms
122 rdf:type schema:DefinedTerm
123 N9d8c529a75b14c2c8c0921653dc65170 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
124 schema:name Dose-Response Relationship, Radiation
125 rdf:type schema:DefinedTerm
126 Na4797ff98e70475f9d9dd888ba097e13 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Software
128 rdf:type schema:DefinedTerm
129 Nb1f9270779094a799ec74e072b6b6a31 schema:issueNumber 1
130 rdf:type schema:PublicationIssue
131 Nbad9cc6055f34a2386d383d47a22937f rdf:first sg:person.0751077254.62
132 rdf:rest N1bf3e22c8e5246c98b0f53a0b69de14b
133 Nbf17fac6b0bf44b9b0d7b8943fd90aa0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Models, Biological
135 rdf:type schema:DefinedTerm
136 Nc5c8e7639bfc4d5bbf6865a552c439c3 schema:name Springer Nature - SN SciGraph project
137 rdf:type schema:Organization
138 Nc83bbdef7e03401394cf82ed52e23ef6 schema:name dimensions_id
139 schema:value pub.1049887481
140 rdf:type schema:PropertyValue
141 Nd4504351317b4876912f16de081ca16f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Cell Cycle
143 rdf:type schema:DefinedTerm
144 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
145 schema:name Biological Sciences
146 rdf:type schema:DefinedTerm
147 sg:grant.2586430 http://pending.schema.org/fundedItem sg:pub.10.1186/1742-4682-3-7
148 rdf:type schema:MonetaryGrant
149 sg:grant.3058693 http://pending.schema.org/fundedItem sg:pub.10.1186/1742-4682-3-7
150 rdf:type schema:MonetaryGrant
151 sg:journal.1034054 schema:issn 1742-4682
152 schema:name Theoretical Biology and Medical Modelling
153 schema:publisher Springer Nature
154 rdf:type schema:Periodical
155 sg:person.01056742320.15 schema:affiliation grid-institutes:grid.411377.7
156 schema:familyName Schnell
157 schema:givenName Santiago
158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01056742320.15
159 rdf:type schema:Person
160 sg:person.01350720433.45 schema:affiliation grid-institutes:grid.412041.2
161 schema:familyName Colin
162 schema:givenName Thierry
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350720433.45
164 rdf:type schema:Person
165 sg:person.0751077254.62 schema:affiliation grid-institutes:grid.25697.3f
166 schema:familyName Ribba
167 schema:givenName Benjamin
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0751077254.62
169 rdf:type schema:Person
170 sg:pub.10.1006/bulm.1998.0042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019334301
171 https://doi.org/10.1006/bulm.1998.0042
172 rdf:type schema:CreativeWork
173 sg:pub.10.1006/bulm.2000.0217 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051771928
174 https://doi.org/10.1006/bulm.2000.0217
175 rdf:type schema:CreativeWork
176 sg:pub.10.1016/j.bulm.2004.06.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029788365
177 https://doi.org/10.1016/j.bulm.2004.06.007
178 rdf:type schema:CreativeWork
179 sg:pub.10.1038/273345a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024073968
180 https://doi.org/10.1038/273345a0
181 rdf:type schema:CreativeWork
182 sg:pub.10.1038/29343 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016163271
183 https://doi.org/10.1038/29343
184 rdf:type schema:CreativeWork
185 sg:pub.10.1038/352345a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007959161
186 https://doi.org/10.1038/352345a0
187 rdf:type schema:CreativeWork
188 sg:pub.10.1038/bjc.1998.503 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031456244
189 https://doi.org/10.1038/bjc.1998.503
190 rdf:type schema:CreativeWork
191 sg:pub.10.1038/nrc795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045099768
192 https://doi.org/10.1038/nrc795
193 rdf:type schema:CreativeWork
194 sg:pub.10.1038/sj.bjc.6602622 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011707440
195 https://doi.org/10.1038/sj.bjc.6602622
196 rdf:type schema:CreativeWork
197 sg:pub.10.1038/sj.onc.1208615 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039884704
198 https://doi.org/10.1038/sj.onc.1208615
199 rdf:type schema:CreativeWork
200 grid-institutes:grid.25697.3f schema:alternateName Institute for Theoretical Medicine and Clinical Pharmacology Department, Faculty of Medicine R.T.H Laennec, University of Lyon, Paradin St., P.O.B 8071, 69376 Lyon Cedex 08, France
201 schema:name Institute for Theoretical Medicine and Clinical Pharmacology Department, Faculty of Medicine R.T.H Laennec, University of Lyon, Paradin St., P.O.B 8071, 69376 Lyon Cedex 08, France
202 rdf:type schema:Organization
203 grid-institutes:grid.411377.7 schema:alternateName Indiana University School of Informatics and Biocomplexity Institute, 1900 East Tenth Street, Eigenmann Hall 906, Bloomington, IN 47406, USA
204 schema:name Indiana University School of Informatics and Biocomplexity Institute, 1900 East Tenth Street, Eigenmann Hall 906, Bloomington, IN 47406, USA
205 rdf:type schema:Organization
206 grid-institutes:grid.412041.2 schema:alternateName Mathématiques Appliquées de Bordeaux, CNRS UMR 5466 and INRIA futurs, University of Bordeaux 1, 351 cours de la liberation, 33405 Talence Cedex, France
207 schema:name Mathématiques Appliquées de Bordeaux, CNRS UMR 5466 and INRIA futurs, University of Bordeaux 1, 351 cours de la liberation, 33405 Talence Cedex, France
208 rdf:type schema:Organization
 




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


...