Phenotypic and Physiological Evaluation for Drought and Salinity Stress Responses in Rice View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012-10-11

AUTHORS

Utlwang Batlang , Niranjan Baisakh , Madana M. R. Ambavaram , Andy Pereira

ABSTRACT

Drought and salinity stresses seriously affect rice plant growth and yield. The growing need to improve rice cultivars for drought and salt tolerance requires the development of reproducible screening methods that simulate field conditions, and which provide quantitative data for statistical testing and selection of genotypes with differential responses. In addition, the study of molecular responses to drought and salt stress requires controlled conditions for growth and treatments that are reportable and comparable between different laboratories. Drought, also known as soil water deficit, can result from insufficient moisture for a plant to grow adequately and complete its life cycle. Salinity due to excess sodium chloride affects rice at seedling and flowering stages, reducing root and leaf growth. Both these abiotic stresses can lead to major physiological and biochemical changes such as reduced photosynthesis and reprogramming of gene expression. The methods presented in this chapter can be applied for (a) examination of stress responses in rice vegetative and reproductive tissues to identify and characterize molecular and physiological responses; (b) testing of candidate genes by overexpression or knockout studies evaluated for altered stress response phenotypes; and (c) screening of different genotypes such as accessions or segregating populations for their quantitative responses to abiotic stress parameters. More... »

PAGES

209-225

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-62703-194-3_15

DOI

http://dx.doi.org/10.1007/978-1-62703-194-3_15

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1003559132

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23135854


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"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0607", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Plant Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adaptation, Biological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Droughts", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Germination", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Oryza", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phenotype", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Photosynthesis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Salinity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Salt Tolerance", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Soil", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Stress, Physiological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Water", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA", 
          "id": "http://www.grid.ac/institutes/grid.438526.e", 
          "name": [
            "Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Batlang", 
        "givenName": "Utlwang", 
        "id": "sg:person.01162344161.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162344161.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA", 
          "id": "http://www.grid.ac/institutes/grid.250060.1", 
          "name": [
            "School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Baisakh", 
        "givenName": "Niranjan", 
        "id": "sg:person.01025010271.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01025010271.93"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA", 
          "id": "http://www.grid.ac/institutes/grid.438526.e", 
          "name": [
            "Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ambavaram", 
        "givenName": "Madana M. R.", 
        "id": "sg:person.01000002361.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000002361.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA", 
          "id": "http://www.grid.ac/institutes/grid.411017.2", 
          "name": [
            "Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA", 
            "Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pereira", 
        "givenName": "Andy", 
        "id": "sg:person.01344430566.76", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344430566.76"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2012-10-11", 
    "datePublishedReg": "2012-10-11", 
    "description": "Drought and salinity stresses seriously affect rice plant growth and yield. The growing need to improve rice cultivars for drought and salt tolerance requires the development of reproducible screening methods that simulate field conditions, and which provide quantitative data for statistical testing and selection of genotypes with differential responses. In addition, the study of molecular responses to drought and salt stress requires controlled conditions for growth and treatments that are reportable and comparable between different laboratories. Drought, also known as soil water deficit, can result from insufficient moisture for a plant to grow adequately and complete its life cycle. Salinity due to excess sodium chloride affects rice at seedling and flowering stages, reducing root and leaf growth. Both these abiotic stresses can lead to major physiological and biochemical changes such as reduced photosynthesis and reprogramming of gene expression. The methods presented in this chapter can be applied for (a) examination of stress responses in rice vegetative and reproductive tissues to identify and characterize molecular and physiological responses; (b) testing of candidate genes by overexpression or knockout studies evaluated for altered stress response phenotypes; and (c) screening of different genotypes such as accessions or segregating populations for their quantitative responses to abiotic stress parameters.", 
    "editor": [
      {
        "familyName": "Yang", 
        "givenName": "Yinong", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-62703-194-3_15", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-1-62703-193-6", 
        "978-1-62703-194-3"
      ], 
      "name": "Rice Protocols", 
      "type": "Book"
    }, 
    "keywords": [
      "stress response", 
      "soil water deficit", 
      "selection of genotypes", 
      "salinity stress response", 
      "rice plant growth", 
      "stress response phenotypes", 
      "reproducible screening method", 
      "salt tolerance", 
      "abiotic stresses", 
      "insufficient moisture", 
      "plant growth", 
      "water deficit", 
      "salt stress", 
      "salinity stress", 
      "leaf growth", 
      "field conditions", 
      "drought", 
      "knockout studies", 
      "gene expression", 
      "rice cultivars", 
      "candidate genes", 
      "reproductive tissues", 
      "rice", 
      "excess sodium chloride", 
      "different genotypes", 
      "molecular response", 
      "response phenotypes", 
      "differential response", 
      "physiological responses", 
      "life cycle", 
      "physiological evaluation", 
      "genotypes", 
      "growth", 
      "biochemical changes", 
      "quantitative response", 
      "reprogramming", 
      "cultivars", 
      "photosynthesis", 
      "yield", 
      "plants", 
      "genes", 
      "moisture", 
      "roots", 
      "accessions", 
      "stress", 
      "phenotypic", 
      "salinity", 
      "tolerance", 
      "overexpression", 
      "phenotype", 
      "screening method", 
      "expression", 
      "response", 
      "selection", 
      "population", 
      "quantitative data", 
      "tissue", 
      "conditions", 
      "sodium chloride", 
      "different laboratories", 
      "cycle", 
      "stage", 
      "deficits", 
      "screening", 
      "development", 
      "stress parameters", 
      "need", 
      "study", 
      "addition", 
      "changes", 
      "laboratory", 
      "treatment", 
      "chapter", 
      "data", 
      "statistical testing", 
      "evaluation", 
      "testing", 
      "method", 
      "chloride", 
      "parameters", 
      "examination", 
      "altered stress response phenotypes", 
      "abiotic stress parameters"
    ], 
    "name": "Phenotypic and Physiological Evaluation for Drought and Salinity Stress Responses in Rice", 
    "pagination": "209-225", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1003559132"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-62703-194-3_15"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "23135854"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-62703-194-3_15", 
      "https://app.dimensions.ai/details/publication/pub.1003559132"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-01-01T19:20", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/chapter/chapter_351.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-1-62703-194-3_15"
  }
]
 

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.10.1007/978-1-62703-194-3_15'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-62703-194-3_15'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-62703-194-3_15'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-62703-194-3_15'


 

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

223 TRIPLES      23 PREDICATES      120 URIs      112 LITERALS      19 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-62703-194-3_15 schema:about N0ee0fcc4c48342ffad1f05682665a61a
2 N11345f3f7b2c471fabbf1893d47af7b5
3 N3bacafbcf69a44d19cd4f35b755e1921
4 N3c66f394b2d0486eb8166101b0913228
5 N41486d61d86a4f33b99bded50314aa4a
6 N6cfd655a40cf4e7e8261f9450e408ff0
7 N7d65b121f757469384c7d6096162be2f
8 Naeeb31b8310e4bad8418cb57911b2e45
9 Nba566062f1c047b5b1d3e485ba61172b
10 Nbc155037f5fd4c72abd972ff0aa834aa
11 Ncda13a50bd2047a599ddd8017e95e5a1
12 anzsrc-for:06
13 anzsrc-for:0604
14 anzsrc-for:0607
15 schema:author Nc3dc731819974983befb53968c309fe5
16 schema:datePublished 2012-10-11
17 schema:datePublishedReg 2012-10-11
18 schema:description Drought and salinity stresses seriously affect rice plant growth and yield. The growing need to improve rice cultivars for drought and salt tolerance requires the development of reproducible screening methods that simulate field conditions, and which provide quantitative data for statistical testing and selection of genotypes with differential responses. In addition, the study of molecular responses to drought and salt stress requires controlled conditions for growth and treatments that are reportable and comparable between different laboratories. Drought, also known as soil water deficit, can result from insufficient moisture for a plant to grow adequately and complete its life cycle. Salinity due to excess sodium chloride affects rice at seedling and flowering stages, reducing root and leaf growth. Both these abiotic stresses can lead to major physiological and biochemical changes such as reduced photosynthesis and reprogramming of gene expression. The methods presented in this chapter can be applied for (a) examination of stress responses in rice vegetative and reproductive tissues to identify and characterize molecular and physiological responses; (b) testing of candidate genes by overexpression or knockout studies evaluated for altered stress response phenotypes; and (c) screening of different genotypes such as accessions or segregating populations for their quantitative responses to abiotic stress parameters.
19 schema:editor N5a28565650074b9491b678ebd7da26a6
20 schema:genre chapter
21 schema:inLanguage en
22 schema:isAccessibleForFree false
23 schema:isPartOf N1f28b7564a654615a726e6c3c074b97f
24 schema:keywords abiotic stress parameters
25 abiotic stresses
26 accessions
27 addition
28 altered stress response phenotypes
29 biochemical changes
30 candidate genes
31 changes
32 chapter
33 chloride
34 conditions
35 cultivars
36 cycle
37 data
38 deficits
39 development
40 different genotypes
41 different laboratories
42 differential response
43 drought
44 evaluation
45 examination
46 excess sodium chloride
47 expression
48 field conditions
49 gene expression
50 genes
51 genotypes
52 growth
53 insufficient moisture
54 knockout studies
55 laboratory
56 leaf growth
57 life cycle
58 method
59 moisture
60 molecular response
61 need
62 overexpression
63 parameters
64 phenotype
65 phenotypic
66 photosynthesis
67 physiological evaluation
68 physiological responses
69 plant growth
70 plants
71 population
72 quantitative data
73 quantitative response
74 reproducible screening method
75 reproductive tissues
76 reprogramming
77 response
78 response phenotypes
79 rice
80 rice cultivars
81 rice plant growth
82 roots
83 salinity
84 salinity stress
85 salinity stress response
86 salt stress
87 salt tolerance
88 screening
89 screening method
90 selection
91 selection of genotypes
92 sodium chloride
93 soil water deficit
94 stage
95 statistical testing
96 stress
97 stress parameters
98 stress response
99 stress response phenotypes
100 study
101 testing
102 tissue
103 tolerance
104 treatment
105 water deficit
106 yield
107 schema:name Phenotypic and Physiological Evaluation for Drought and Salinity Stress Responses in Rice
108 schema:pagination 209-225
109 schema:productId N734c7146cacb41eba218edc5a7c4f70f
110 N7777e0be70ae47d6891a68754e3d9a5b
111 Na3806415ae5042f59bcd1b098a42790b
112 schema:publisher Nc6769926b123439290b27703a83be9d1
113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003559132
114 https://doi.org/10.1007/978-1-62703-194-3_15
115 schema:sdDatePublished 2022-01-01T19:20
116 schema:sdLicense https://scigraph.springernature.com/explorer/license/
117 schema:sdPublisher N2bd14e531fb74c33843647805cc87515
118 schema:url https://doi.org/10.1007/978-1-62703-194-3_15
119 sgo:license sg:explorer/license/
120 sgo:sdDataset chapters
121 rdf:type schema:Chapter
122 N04a9dd75f5c44c1b88129db9c231511d rdf:first sg:person.01344430566.76
123 rdf:rest rdf:nil
124 N087d572b8b2c487fb8178e5b04dfb7a1 rdf:first sg:person.01000002361.29
125 rdf:rest N04a9dd75f5c44c1b88129db9c231511d
126 N0ee0fcc4c48342ffad1f05682665a61a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Phenotype
128 rdf:type schema:DefinedTerm
129 N0f4de178ef6f4cc28b775170689a58e3 rdf:first sg:person.01025010271.93
130 rdf:rest N087d572b8b2c487fb8178e5b04dfb7a1
131 N11345f3f7b2c471fabbf1893d47af7b5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Soil
133 rdf:type schema:DefinedTerm
134 N196ed1ea66924bbf96c4610fbcabb7bb schema:familyName Yang
135 schema:givenName Yinong
136 rdf:type schema:Person
137 N1f28b7564a654615a726e6c3c074b97f schema:isbn 978-1-62703-193-6
138 978-1-62703-194-3
139 schema:name Rice Protocols
140 rdf:type schema:Book
141 N2bd14e531fb74c33843647805cc87515 schema:name Springer Nature - SN SciGraph project
142 rdf:type schema:Organization
143 N3bacafbcf69a44d19cd4f35b755e1921 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
144 schema:name Droughts
145 rdf:type schema:DefinedTerm
146 N3c66f394b2d0486eb8166101b0913228 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
147 schema:name Salinity
148 rdf:type schema:DefinedTerm
149 N41486d61d86a4f33b99bded50314aa4a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Photosynthesis
151 rdf:type schema:DefinedTerm
152 N5a28565650074b9491b678ebd7da26a6 rdf:first N196ed1ea66924bbf96c4610fbcabb7bb
153 rdf:rest rdf:nil
154 N6cfd655a40cf4e7e8261f9450e408ff0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Stress, Physiological
156 rdf:type schema:DefinedTerm
157 N734c7146cacb41eba218edc5a7c4f70f schema:name dimensions_id
158 schema:value pub.1003559132
159 rdf:type schema:PropertyValue
160 N7777e0be70ae47d6891a68754e3d9a5b schema:name pubmed_id
161 schema:value 23135854
162 rdf:type schema:PropertyValue
163 N7d65b121f757469384c7d6096162be2f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
164 schema:name Germination
165 rdf:type schema:DefinedTerm
166 Na3806415ae5042f59bcd1b098a42790b schema:name doi
167 schema:value 10.1007/978-1-62703-194-3_15
168 rdf:type schema:PropertyValue
169 Naeeb31b8310e4bad8418cb57911b2e45 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
170 schema:name Adaptation, Biological
171 rdf:type schema:DefinedTerm
172 Nba566062f1c047b5b1d3e485ba61172b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
173 schema:name Salt Tolerance
174 rdf:type schema:DefinedTerm
175 Nbc155037f5fd4c72abd972ff0aa834aa schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
176 schema:name Water
177 rdf:type schema:DefinedTerm
178 Nc3dc731819974983befb53968c309fe5 rdf:first sg:person.01162344161.04
179 rdf:rest N0f4de178ef6f4cc28b775170689a58e3
180 Nc6769926b123439290b27703a83be9d1 schema:name Springer Nature
181 rdf:type schema:Organisation
182 Ncda13a50bd2047a599ddd8017e95e5a1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
183 schema:name Oryza
184 rdf:type schema:DefinedTerm
185 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
186 schema:name Biological Sciences
187 rdf:type schema:DefinedTerm
188 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
189 schema:name Genetics
190 rdf:type schema:DefinedTerm
191 anzsrc-for:0607 schema:inDefinedTermSet anzsrc-for:
192 schema:name Plant Biology
193 rdf:type schema:DefinedTerm
194 sg:person.01000002361.29 schema:affiliation grid-institutes:grid.438526.e
195 schema:familyName Ambavaram
196 schema:givenName Madana M. R.
197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000002361.29
198 rdf:type schema:Person
199 sg:person.01025010271.93 schema:affiliation grid-institutes:grid.250060.1
200 schema:familyName Baisakh
201 schema:givenName Niranjan
202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01025010271.93
203 rdf:type schema:Person
204 sg:person.01162344161.04 schema:affiliation grid-institutes:grid.438526.e
205 schema:familyName Batlang
206 schema:givenName Utlwang
207 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162344161.04
208 rdf:type schema:Person
209 sg:person.01344430566.76 schema:affiliation grid-institutes:grid.411017.2
210 schema:familyName Pereira
211 schema:givenName Andy
212 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344430566.76
213 rdf:type schema:Person
214 grid-institutes:grid.250060.1 schema:alternateName School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA
215 schema:name School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA
216 rdf:type schema:Organization
217 grid-institutes:grid.411017.2 schema:alternateName Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
218 schema:name Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
219 Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA
220 rdf:type schema:Organization
221 grid-institutes:grid.438526.e schema:alternateName Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA
222 schema:name Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA
223 rdf:type schema:Organization
 




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


...