Reliable reconstruction of HIV-1 whole genome haplotypes reveals clonal interference and genetic hitchhiking among immune escape variants View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-07-04

AUTHORS

Aridaman Pandit, Rob J de Boer

ABSTRACT

BackgroundFollowing transmission, HIV-1 evolves into a diverse population, and next generation sequencing enables us to detect variants occurring at low frequencies. Studying viral evolution at the level of whole genomes was hitherto not possible because next generation sequencing delivers relatively short reads.ResultsWe here provide a proof of principle that whole HIV-1 genomes can be reliably reconstructed from short reads, and use this to study the selection of immune escape mutations at the level of whole genome haplotypes. Using realistically simulated HIV-1 populations, we demonstrate that reconstruction of complete genome haplotypes is feasible with high fidelity. We do not reconstruct all genetically distinct genomes, but each reconstructed haplotype represents one or more of the quasispecies in the HIV-1 population. We then reconstruct 30 whole genome haplotypes from published short sequence reads sampled longitudinally from a single HIV-1 infected patient. We confirm the reliability of the reconstruction by validating our predicted haplotype genes with single genome amplification sequences, and by comparing haplotype frequencies with observed epitope escape frequencies.ConclusionsPhylogenetic analysis shows that the HIV-1 population undergoes selection driven evolution, with successive replacement of the viral population by novel dominant strains. We demonstrate that immune escape mutants evolve in a dependent manner with various mutations hitchhiking along with others. As a consequence of this clonal interference, selection coefficients have to be estimated for complete haplotypes and not for individual immune escapes. More... »

PAGES

56

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1742-4690-11-56

DOI

http://dx.doi.org/10.1186/1742-4690-11-56

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034235960

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24996694


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/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Epitopes, T-Lymphocyte", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genome, Viral", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "HIV-1", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Haplotypes", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Immune Evasion", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phylogeny", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "T-Lymphocytes, Cytotoxic", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584, Utrecht, CH, The Netherlands", 
          "id": "http://www.grid.ac/institutes/grid.5477.1", 
          "name": [
            "Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584, Utrecht, CH, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pandit", 
        "givenName": "Aridaman", 
        "id": "sg:person.0670377564.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0670377564.23"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584, Utrecht, CH, The Netherlands", 
          "id": "http://www.grid.ac/institutes/grid.5477.1", 
          "name": [
            "Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584, Utrecht, CH, 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.10.1186/1471-2105-12-119", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038990948", 
          "https://doi.org/10.1186/1471-2105-12-119"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nri2674", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029331458", 
          "https://doi.org/10.1038/nri2674"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13087", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010162673", 
          "https://doi.org/10.1038/nature13087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature12344", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020580356", 
          "https://doi.org/10.1038/nature12344"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep02837", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034652514", 
          "https://doi.org/10.1038/srep02837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00109-012-0892-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050701040", 
          "https://doi.org/10.1007/s00109-012-0892-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1742-4690-9-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017509438", 
          "https://doi.org/10.1186/1742-4690-9-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1742-4690-9-89", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031512000", 
          "https://doi.org/10.1186/1742-4690-9-89"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-07-04", 
    "datePublishedReg": "2014-07-04", 
    "description": "BackgroundFollowing transmission, HIV-1 evolves into a diverse population, and next generation sequencing enables us to detect variants occurring at low frequencies. Studying viral evolution at the level of whole genomes was hitherto not possible because next generation sequencing delivers relatively short reads.ResultsWe here provide a proof of principle that whole HIV-1 genomes can be reliably reconstructed from short reads, and use this to study the selection of immune escape mutations at the level of whole genome haplotypes. Using realistically simulated HIV-1 populations, we demonstrate that reconstruction of complete genome haplotypes is feasible with high fidelity. We do not reconstruct all genetically distinct genomes, but each reconstructed haplotype represents one or more of the quasispecies in the HIV-1 population. We then reconstruct 30 whole genome haplotypes from published short sequence reads sampled longitudinally from a single HIV-1 infected patient. We confirm the reliability of the reconstruction by validating our predicted haplotype genes with single genome amplification sequences, and by comparing haplotype frequencies with observed epitope escape frequencies.ConclusionsPhylogenetic analysis shows that the HIV-1 population undergoes selection driven evolution, with successive replacement of the viral population by novel dominant strains. We demonstrate that immune escape mutants evolve in a dependent manner with various mutations hitchhiking along with others. As a consequence of this clonal interference, selection coefficients have to be estimated for complete haplotypes and not for individual immune escapes.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/1742-4690-11-56", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1033800", 
        "issn": [
          "1742-4690"
        ], 
        "name": "Retrovirology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "11"
      }
    ], 
    "keywords": [
      "whole-genome haplotypes", 
      "clonal interference", 
      "short reads", 
      "short sequence reads", 
      "genetic hitchhiking", 
      "distinct genomes", 
      "next-generation sequencing", 
      "selection coefficients", 
      "whole genome", 
      "sequence reads", 
      "genome", 
      "haplotype genes", 
      "viral evolution", 
      "HIV-1 populations", 
      "HIV-1 genome", 
      "generation sequencing", 
      "complete haplotypes", 
      "viral populations", 
      "haplotypes", 
      "reconstructed haplotypes", 
      "reads", 
      "dependent manner", 
      "amplification sequence", 
      "haplotype frequencies", 
      "HIV-1 evolves", 
      "single HIV-1", 
      "proof of principle", 
      "mutations", 
      "immune escape mutations", 
      "immune escape variants", 
      "immune escape mutants", 
      "dominant strain", 
      "hitchhiking", 
      "mutants", 
      "escape mutations", 
      "escape variants", 
      "immune escape", 
      "HIV-1", 
      "genes", 
      "escape mutants", 
      "variants", 
      "population", 
      "sequencing", 
      "evolution", 
      "diverse populations", 
      "selection", 
      "sequence", 
      "successive replacement", 
      "high fidelity", 
      "quasispecies", 
      "strains", 
      "escape frequency", 
      "levels", 
      "manner", 
      "ResultsWe", 
      "fidelity", 
      "escape", 
      "interference", 
      "consequences", 
      "low frequency", 
      "reconstruction", 
      "frequency", 
      "replacement", 
      "analysis", 
      "evolves", 
      "reliable reconstruction", 
      "transmission", 
      "delivers", 
      "reliability", 
      "proof", 
      "principles", 
      "coefficient"
    ], 
    "name": "Reliable reconstruction of HIV-1 whole genome haplotypes reveals clonal interference and genetic hitchhiking among immune escape variants", 
    "pagination": "56", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1034235960"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1742-4690-11-56"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "24996694"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1742-4690-11-56", 
      "https://app.dimensions.ai/details/publication/pub.1034235960"
    ], 
    "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_620.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/1742-4690-11-56"
  }
]
 

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.10.1186/1742-4690-11-56'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1742-4690-11-56'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1742-4690-11-56'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1742-4690-11-56'


 

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

203 TRIPLES      21 PREDICATES      113 URIs      97 LITERALS      15 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1742-4690-11-56 schema:about N0f753d9d8c1c46129e4ea859ba3190bc
2 N28c8b1582c02442db107caf7777b327d
3 N36ffbbc57fca4971bb706d01d3aa2432
4 N4a5e95df3392484c96526cd7c7cb8389
5 N77b2a1f8d9904375896c45f6b9a4657f
6 N8010e7f5037d4779bd8b8a1e99d58b0b
7 N96b70c71536d4307906f14ed2ced3aa4
8 Na7308206c89143a19f82e6336bf1cdc1
9 anzsrc-for:11
10 anzsrc-for:1103
11 schema:author N9b88b091e06c49ddb838afbcf7c35756
12 schema:citation sg:pub.10.1007/s00109-012-0892-1
13 sg:pub.10.1038/nature12344
14 sg:pub.10.1038/nature13087
15 sg:pub.10.1038/nri2674
16 sg:pub.10.1038/srep02837
17 sg:pub.10.1186/1471-2105-12-119
18 sg:pub.10.1186/1742-4690-9-1
19 sg:pub.10.1186/1742-4690-9-89
20 schema:datePublished 2014-07-04
21 schema:datePublishedReg 2014-07-04
22 schema:description BackgroundFollowing transmission, HIV-1 evolves into a diverse population, and next generation sequencing enables us to detect variants occurring at low frequencies. Studying viral evolution at the level of whole genomes was hitherto not possible because next generation sequencing delivers relatively short reads.ResultsWe here provide a proof of principle that whole HIV-1 genomes can be reliably reconstructed from short reads, and use this to study the selection of immune escape mutations at the level of whole genome haplotypes. Using realistically simulated HIV-1 populations, we demonstrate that reconstruction of complete genome haplotypes is feasible with high fidelity. We do not reconstruct all genetically distinct genomes, but each reconstructed haplotype represents one or more of the quasispecies in the HIV-1 population. We then reconstruct 30 whole genome haplotypes from published short sequence reads sampled longitudinally from a single HIV-1 infected patient. We confirm the reliability of the reconstruction by validating our predicted haplotype genes with single genome amplification sequences, and by comparing haplotype frequencies with observed epitope escape frequencies.ConclusionsPhylogenetic analysis shows that the HIV-1 population undergoes selection driven evolution, with successive replacement of the viral population by novel dominant strains. We demonstrate that immune escape mutants evolve in a dependent manner with various mutations hitchhiking along with others. As a consequence of this clonal interference, selection coefficients have to be estimated for complete haplotypes and not for individual immune escapes.
23 schema:genre article
24 schema:isAccessibleForFree true
25 schema:isPartOf N27994eaca0fa43559f50d5bead4a4469
26 N6ecf41d3da4647ea909fd8cc375cfc7f
27 sg:journal.1033800
28 schema:keywords HIV-1
29 HIV-1 evolves
30 HIV-1 genome
31 HIV-1 populations
32 ResultsWe
33 amplification sequence
34 analysis
35 clonal interference
36 coefficient
37 complete haplotypes
38 consequences
39 delivers
40 dependent manner
41 distinct genomes
42 diverse populations
43 dominant strain
44 escape
45 escape frequency
46 escape mutants
47 escape mutations
48 escape variants
49 evolution
50 evolves
51 fidelity
52 frequency
53 generation sequencing
54 genes
55 genetic hitchhiking
56 genome
57 haplotype frequencies
58 haplotype genes
59 haplotypes
60 high fidelity
61 hitchhiking
62 immune escape
63 immune escape mutants
64 immune escape mutations
65 immune escape variants
66 interference
67 levels
68 low frequency
69 manner
70 mutants
71 mutations
72 next-generation sequencing
73 population
74 principles
75 proof
76 proof of principle
77 quasispecies
78 reads
79 reconstructed haplotypes
80 reconstruction
81 reliability
82 reliable reconstruction
83 replacement
84 selection
85 selection coefficients
86 sequence
87 sequence reads
88 sequencing
89 short reads
90 short sequence reads
91 single HIV-1
92 strains
93 successive replacement
94 transmission
95 variants
96 viral evolution
97 viral populations
98 whole genome
99 whole-genome haplotypes
100 schema:name Reliable reconstruction of HIV-1 whole genome haplotypes reveals clonal interference and genetic hitchhiking among immune escape variants
101 schema:pagination 56
102 schema:productId N7394b168f8cc43c293fc7d1eeda828bb
103 N75c66109352c42cc939a29b855c71774
104 N9f298fa1a92e4d7b9d73b6c05560fb5b
105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034235960
106 https://doi.org/10.1186/1742-4690-11-56
107 schema:sdDatePublished 2022-09-02T15:57
108 schema:sdLicense https://scigraph.springernature.com/explorer/license/
109 schema:sdPublisher N77b2275710aa4fb49690cc56701d786f
110 schema:url https://doi.org/10.1186/1742-4690-11-56
111 sgo:license sg:explorer/license/
112 sgo:sdDataset articles
113 rdf:type schema:ScholarlyArticle
114 N0f753d9d8c1c46129e4ea859ba3190bc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Haplotypes
116 rdf:type schema:DefinedTerm
117 N27994eaca0fa43559f50d5bead4a4469 schema:issueNumber 1
118 rdf:type schema:PublicationIssue
119 N28c8b1582c02442db107caf7777b327d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Epitopes, T-Lymphocyte
121 rdf:type schema:DefinedTerm
122 N36ffbbc57fca4971bb706d01d3aa2432 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name HIV-1
124 rdf:type schema:DefinedTerm
125 N4a5e95df3392484c96526cd7c7cb8389 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Phylogeny
127 rdf:type schema:DefinedTerm
128 N6ecf41d3da4647ea909fd8cc375cfc7f schema:volumeNumber 11
129 rdf:type schema:PublicationVolume
130 N7394b168f8cc43c293fc7d1eeda828bb schema:name dimensions_id
131 schema:value pub.1034235960
132 rdf:type schema:PropertyValue
133 N75c66109352c42cc939a29b855c71774 schema:name doi
134 schema:value 10.1186/1742-4690-11-56
135 rdf:type schema:PropertyValue
136 N77b2275710aa4fb49690cc56701d786f schema:name Springer Nature - SN SciGraph project
137 rdf:type schema:Organization
138 N77b2a1f8d9904375896c45f6b9a4657f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Humans
140 rdf:type schema:DefinedTerm
141 N8010e7f5037d4779bd8b8a1e99d58b0b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name T-Lymphocytes, Cytotoxic
143 rdf:type schema:DefinedTerm
144 N96b70c71536d4307906f14ed2ced3aa4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name Genome, Viral
146 rdf:type schema:DefinedTerm
147 N9b88b091e06c49ddb838afbcf7c35756 rdf:first sg:person.0670377564.23
148 rdf:rest Nf96bac425aae4ad992bc4e417199b604
149 N9f298fa1a92e4d7b9d73b6c05560fb5b schema:name pubmed_id
150 schema:value 24996694
151 rdf:type schema:PropertyValue
152 Na7308206c89143a19f82e6336bf1cdc1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
153 schema:name Immune Evasion
154 rdf:type schema:DefinedTerm
155 Nf96bac425aae4ad992bc4e417199b604 rdf:first sg:person.0774503452.97
156 rdf:rest rdf:nil
157 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
158 schema:name Medical and Health Sciences
159 rdf:type schema:DefinedTerm
160 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
161 schema:name Clinical Sciences
162 rdf:type schema:DefinedTerm
163 sg:journal.1033800 schema:issn 1742-4690
164 schema:name Retrovirology
165 schema:publisher Springer Nature
166 rdf:type schema:Periodical
167 sg:person.0670377564.23 schema:affiliation grid-institutes:grid.5477.1
168 schema:familyName Pandit
169 schema:givenName Aridaman
170 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0670377564.23
171 rdf:type schema:Person
172 sg:person.0774503452.97 schema:affiliation grid-institutes:grid.5477.1
173 schema:familyName de Boer
174 schema:givenName Rob J
175 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774503452.97
176 rdf:type schema:Person
177 sg:pub.10.1007/s00109-012-0892-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050701040
178 https://doi.org/10.1007/s00109-012-0892-1
179 rdf:type schema:CreativeWork
180 sg:pub.10.1038/nature12344 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020580356
181 https://doi.org/10.1038/nature12344
182 rdf:type schema:CreativeWork
183 sg:pub.10.1038/nature13087 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010162673
184 https://doi.org/10.1038/nature13087
185 rdf:type schema:CreativeWork
186 sg:pub.10.1038/nri2674 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029331458
187 https://doi.org/10.1038/nri2674
188 rdf:type schema:CreativeWork
189 sg:pub.10.1038/srep02837 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034652514
190 https://doi.org/10.1038/srep02837
191 rdf:type schema:CreativeWork
192 sg:pub.10.1186/1471-2105-12-119 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038990948
193 https://doi.org/10.1186/1471-2105-12-119
194 rdf:type schema:CreativeWork
195 sg:pub.10.1186/1742-4690-9-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017509438
196 https://doi.org/10.1186/1742-4690-9-1
197 rdf:type schema:CreativeWork
198 sg:pub.10.1186/1742-4690-9-89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031512000
199 https://doi.org/10.1186/1742-4690-9-89
200 rdf:type schema:CreativeWork
201 grid-institutes:grid.5477.1 schema:alternateName Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584, Utrecht, CH, The Netherlands
202 schema:name Theoretical Biology and Bioinformatics, Utrecht University, Padualaan 8, 3584, Utrecht, CH, The Netherlands
203 rdf:type schema:Organization
 




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


...