Statistical techniques for detection of major genes in animal breeding data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1988-08

AUTHORS

I. Hoeschele

ABSTRACT

Statistical techniques for detection of major loci and for making inferences about major locus parameters such as genotypic frequencies, effects and gene action from field-collected data are presented. In field data, major genotypic effects are likely to be masked by a large number of environmental differences in addition to additive and nonadditive polygenic effects. A graphical technique and a procedure for discriminating among genetic hypotheses based on a mixed model accounting for all these factors are proposed. The methods are illustrated by using simulated data. More... »

PAGES

311-319

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf00257861

DOI

http://dx.doi.org/10.1007/bf00257861

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014731958

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24232121


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/2008/07", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Agricultural and Veterinary Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/10", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Technology", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Animal Science, Iowa State University, 50011, Ames, IA, USA", 
          "id": "http://www.grid.ac/institutes/grid.34421.30", 
          "name": [
            "Department of Animal Science, Iowa State University, 50011, Ames, IA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hoeschele", 
        "givenName": "I.", 
        "id": "sg:person.01326432717.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01326432717.41"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf00288836", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032322612", 
          "https://doi.org/10.1007/bf00288836"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1297-9686-15-2-201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040377019", 
          "https://doi.org/10.1186/1297-9686-15-2-201"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1988-08", 
    "datePublishedReg": "1988-08-01", 
    "description": "Statistical techniques for detection of major loci and for making inferences about major locus parameters such as genotypic frequencies, effects and gene action from field-collected data are presented. In field data, major genotypic effects are likely to be masked by a large number of environmental differences in addition to additive and nonadditive polygenic effects. A graphical technique and a procedure for discriminating among genetic hypotheses based on a mixed model accounting for all these factors are proposed. The methods are illustrated by using simulated data.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/bf00257861", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1135804", 
        "issn": [
          "0040-5752", 
          "1432-2242"
        ], 
        "name": "Theoretical and Applied Genetics", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "76"
      }
    ], 
    "keywords": [
      "statistical techniques", 
      "animal breeding data", 
      "gene action", 
      "major gene", 
      "major locus", 
      "breeding data", 
      "polygenic effects", 
      "genotypic effects", 
      "environmental differences", 
      "field-collected data", 
      "genetic hypothesis", 
      "genotypic frequencies", 
      "graphical techniques", 
      "genes", 
      "loci", 
      "field data", 
      "mixed models", 
      "large number", 
      "inference", 
      "technique", 
      "parameters", 
      "hypothesis", 
      "model", 
      "effect", 
      "data", 
      "number", 
      "action", 
      "addition", 
      "factors", 
      "frequency", 
      "procedure", 
      "differences", 
      "detection", 
      "method", 
      "major locus parameters", 
      "locus parameters", 
      "major genotypic effects", 
      "nonadditive polygenic effects"
    ], 
    "name": "Statistical techniques for detection of major genes in animal breeding data", 
    "pagination": "311-319", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1014731958"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf00257861"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "24232121"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf00257861", 
      "https://app.dimensions.ai/details/publication/pub.1014731958"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:03", 
    "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/article/article_198.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/bf00257861"
  }
]
 

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/bf00257861'

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/bf00257861'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf00257861'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf00257861'


 

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

112 TRIPLES      22 PREDICATES      68 URIs      57 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf00257861 schema:about anzsrc-for:06
2 anzsrc-for:07
3 anzsrc-for:10
4 schema:author N56737e1972644c7ab1a6b7387cc867cb
5 schema:citation sg:pub.10.1007/bf00288836
6 sg:pub.10.1186/1297-9686-15-2-201
7 schema:datePublished 1988-08
8 schema:datePublishedReg 1988-08-01
9 schema:description Statistical techniques for detection of major loci and for making inferences about major locus parameters such as genotypic frequencies, effects and gene action from field-collected data are presented. In field data, major genotypic effects are likely to be masked by a large number of environmental differences in addition to additive and nonadditive polygenic effects. A graphical technique and a procedure for discriminating among genetic hypotheses based on a mixed model accounting for all these factors are proposed. The methods are illustrated by using simulated data.
10 schema:genre article
11 schema:inLanguage en
12 schema:isAccessibleForFree false
13 schema:isPartOf N5a02f4a66cef43ba9d16764986923823
14 Ncfce489846664f9296e1403fe0b9a1f3
15 sg:journal.1135804
16 schema:keywords action
17 addition
18 animal breeding data
19 breeding data
20 data
21 detection
22 differences
23 effect
24 environmental differences
25 factors
26 field data
27 field-collected data
28 frequency
29 gene action
30 genes
31 genetic hypothesis
32 genotypic effects
33 genotypic frequencies
34 graphical techniques
35 hypothesis
36 inference
37 large number
38 loci
39 locus parameters
40 major gene
41 major genotypic effects
42 major locus
43 major locus parameters
44 method
45 mixed models
46 model
47 nonadditive polygenic effects
48 number
49 parameters
50 polygenic effects
51 procedure
52 statistical techniques
53 technique
54 schema:name Statistical techniques for detection of major genes in animal breeding data
55 schema:pagination 311-319
56 schema:productId N4eba6096e9854b7aa909a69f997a603f
57 N7964ea92ebc142abb16aa35c48738239
58 Nd6707e953ca54100864c3157af606baf
59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014731958
60 https://doi.org/10.1007/bf00257861
61 schema:sdDatePublished 2022-01-01T18:03
62 schema:sdLicense https://scigraph.springernature.com/explorer/license/
63 schema:sdPublisher N0fb0e38841a3458f8850a570cbb26360
64 schema:url https://doi.org/10.1007/bf00257861
65 sgo:license sg:explorer/license/
66 sgo:sdDataset articles
67 rdf:type schema:ScholarlyArticle
68 N0fb0e38841a3458f8850a570cbb26360 schema:name Springer Nature - SN SciGraph project
69 rdf:type schema:Organization
70 N4eba6096e9854b7aa909a69f997a603f schema:name doi
71 schema:value 10.1007/bf00257861
72 rdf:type schema:PropertyValue
73 N56737e1972644c7ab1a6b7387cc867cb rdf:first sg:person.01326432717.41
74 rdf:rest rdf:nil
75 N5a02f4a66cef43ba9d16764986923823 schema:issueNumber 2
76 rdf:type schema:PublicationIssue
77 N7964ea92ebc142abb16aa35c48738239 schema:name pubmed_id
78 schema:value 24232121
79 rdf:type schema:PropertyValue
80 Ncfce489846664f9296e1403fe0b9a1f3 schema:volumeNumber 76
81 rdf:type schema:PublicationVolume
82 Nd6707e953ca54100864c3157af606baf schema:name dimensions_id
83 schema:value pub.1014731958
84 rdf:type schema:PropertyValue
85 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
86 schema:name Biological Sciences
87 rdf:type schema:DefinedTerm
88 anzsrc-for:07 schema:inDefinedTermSet anzsrc-for:
89 schema:name Agricultural and Veterinary Sciences
90 rdf:type schema:DefinedTerm
91 anzsrc-for:10 schema:inDefinedTermSet anzsrc-for:
92 schema:name Technology
93 rdf:type schema:DefinedTerm
94 sg:journal.1135804 schema:issn 0040-5752
95 1432-2242
96 schema:name Theoretical and Applied Genetics
97 schema:publisher Springer Nature
98 rdf:type schema:Periodical
99 sg:person.01326432717.41 schema:affiliation grid-institutes:grid.34421.30
100 schema:familyName Hoeschele
101 schema:givenName I.
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01326432717.41
103 rdf:type schema:Person
104 sg:pub.10.1007/bf00288836 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032322612
105 https://doi.org/10.1007/bf00288836
106 rdf:type schema:CreativeWork
107 sg:pub.10.1186/1297-9686-15-2-201 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040377019
108 https://doi.org/10.1186/1297-9686-15-2-201
109 rdf:type schema:CreativeWork
110 grid-institutes:grid.34421.30 schema:alternateName Department of Animal Science, Iowa State University, 50011, Ames, IA, USA
111 schema:name Department of Animal Science, Iowa State University, 50011, Ames, IA, USA
112 rdf:type schema:Organization
 




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


...