CloudTSS: A TagSNP Selection Approach on Cloud Computing View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Che-Lun Hung , Yaw-Ling Lin , Guan-Jie Hua , Yu-Chen Hu

ABSTRACT

SNPs are fundamental roles for various applications including medical diagnostic, phylogenies and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Genetic variants that are near each other tend to be inherited together; these regions of linked variants are known as haplotypes. Recently, genetics researches revealed that SNPs within certain haplotype blocks induce only a few distinct common haplotypes in the majority of the population. The existence of haplotype block structure has serious implications for association-based methods for the mapping of disease genes. This paper proposes a parallel haplotype block partition and SNPs selection method under a diversity function by using the Hadoop MapReduce framework. The experiment shows that the proposed MapReduce-paralleled combinatorial algorithm performs well on the real-world data obtained in from the HapMap data set; the computation efficiency can be significantly improved proportional to the number of processors being used. More... »

PAGES

525-534

Book

TITLE

Grid and Distributed Computing

ISBN

978-3-642-27179-3
978-3-642-27180-9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-27180-9_64

DOI

http://dx.doi.org/10.1007/978-3-642-27180-9_64

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026543934


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/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Providence University", 
          "id": "https://www.grid.ac/institutes/grid.412550.7", 
          "name": [
            "Dept. of Computer Science & Communication Engineering, Providence University, 200 Chung Chi Rd., Taichung, 43301, Republic of China, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hung", 
        "givenName": "Che-Lun", 
        "id": "sg:person.01336120166.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01336120166.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Providence University", 
          "id": "https://www.grid.ac/institutes/grid.412550.7", 
          "name": [
            "Dept. of Computer Science & Information Management, Providence University, 200 Chung Chi Rd., Taichung, 43301, Republic of China, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lin", 
        "givenName": "Yaw-Ling", 
        "id": "sg:person.01032717740.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01032717740.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Providence University", 
          "id": "https://www.grid.ac/institutes/grid.412550.7", 
          "name": [
            "Dept. of Computer Science & Information Management, Providence University, 200 Chung Chi Rd., Taichung, 43301, Republic of China, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hua", 
        "givenName": "Guan-Jie", 
        "id": "sg:person.01055745073.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01055745073.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Providence University", 
          "id": "https://www.grid.ac/institutes/grid.412550.7", 
          "name": [
            "Dept. of Computer Science & Information Management, Providence University, 200 Chung Chi Rd., Taichung, 43301, Republic of China, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hu", 
        "givenName": "Yu-Chen", 
        "id": "sg:person.012113441135.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012113441135.19"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1093/bioinformatics/bth907", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005165631"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1629175.1629198", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006814493"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0959-4388(00)00261-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008356697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1069424", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010139737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000073729", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014435426"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1001-233", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017573512", 
          "https://doi.org/10.1038/ng1001-233"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1001-233", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017573512", 
          "https://doi.org/10.1038/ng1001-233"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.mp.4001779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023011769", 
          "https://doi.org/10.1038/sj.mp.4001779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.mp.4001779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023011769", 
          "https://doi.org/10.1038/sj.mp.4001779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1001-229", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026787741", 
          "https://doi.org/10.1038/ng1001-229"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng1001-229", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026787741", 
          "https://doi.org/10.1038/ng1001-229"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jbi.2010.05.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027321888"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp236", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029688589"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jtbi.2010.08.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029981129"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-6-303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035277876", 
          "https://doi.org/10.1186/1471-2105-6-303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.483802", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037792121"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature00864", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040675195", 
          "https://doi.org/10.1038/nature00864"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature00864", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040675195", 
          "https://doi.org/10.1038/nature00864"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/hmg/9.16.2403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041769869"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-11-s12-s1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044778751", 
          "https://doi.org/10.1186/1471-2105-11-s12-s1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.1837404", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047213321"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-69733-6_31", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047382730", 
          "https://doi.org/10.1007/978-3-540-69733-6_31"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.humimm.2005.10.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049231837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.humimm.2005.10.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049231837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/344398", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058640423"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/344398", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058640423"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/344780", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058640580"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/344780", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058640580"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/377106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058670200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/377106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058670200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/378099", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058671155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/378099", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058671155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1065573", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062445519"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1080090263", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011", 
    "datePublishedReg": "2011-01-01", 
    "description": "SNPs are fundamental roles for various applications including medical diagnostic, phylogenies and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Genetic variants that are near each other tend to be inherited together; these regions of linked variants are known as haplotypes. Recently, genetics researches revealed that SNPs within certain haplotype blocks induce only a few distinct common haplotypes in the majority of the population. The existence of haplotype block structure has serious implications for association-based methods for the mapping of disease genes. This paper proposes a parallel haplotype block partition and SNPs selection method under a diversity function by using the Hadoop MapReduce framework. The experiment shows that the proposed MapReduce-paralleled combinatorial algorithm performs well on the real-world data obtained in from the HapMap data set; the computation efficiency can be significantly improved proportional to the number of processors being used.", 
    "editor": [
      {
        "familyName": "Kim", 
        "givenName": "Tai-hoon", 
        "type": "Person"
      }, 
      {
        "familyName": "Adeli", 
        "givenName": "Hojjat", 
        "type": "Person"
      }, 
      {
        "familyName": "Cho", 
        "givenName": "Hyun-seob", 
        "type": "Person"
      }, 
      {
        "familyName": "Gervasi", 
        "givenName": "Osvaldo", 
        "type": "Person"
      }, 
      {
        "familyName": "Yau", 
        "givenName": "Stephen S.", 
        "type": "Person"
      }, 
      {
        "familyName": "Kang", 
        "givenName": "Byeong-Ho", 
        "type": "Person"
      }, 
      {
        "familyName": "Villalba", 
        "givenName": "Javier Garc\u00eda", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-27180-9_64", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-27179-3", 
        "978-3-642-27180-9"
      ], 
      "name": "Grid and Distributed Computing", 
      "type": "Book"
    }, 
    "name": "CloudTSS: A TagSNP Selection Approach on Cloud Computing", 
    "pagination": "525-534", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-27180-9_64"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "7e74d8372f6b2a1dd337c92b1fc4be9c693eb8266bf2350b7829eb29c404ba18"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1026543934"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-27180-9_64", 
      "https://app.dimensions.ai/details/publication/pub.1026543934"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T20:10", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000288.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-642-27180-9_64"
  }
]
 

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.10.1007/978-3-642-27180-9_64'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-27180-9_64'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-27180-9_64'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-27180-9_64'


 

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

198 TRIPLES      23 PREDICATES      52 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-27180-9_64 schema:about anzsrc-for:06
2 anzsrc-for:0604
3 schema:author N572dd6fe65364fe9ad90bc2e0f61db2f
4 schema:citation sg:pub.10.1007/978-3-540-69733-6_31
5 sg:pub.10.1038/nature00864
6 sg:pub.10.1038/ng1001-229
7 sg:pub.10.1038/ng1001-233
8 sg:pub.10.1038/sj.mp.4001779
9 sg:pub.10.1186/1471-2105-11-s12-s1
10 sg:pub.10.1186/1471-2105-6-303
11 https://app.dimensions.ai/details/publication/pub.1080090263
12 https://doi.org/10.1016/j.humimm.2005.10.001
13 https://doi.org/10.1016/j.jbi.2010.05.011
14 https://doi.org/10.1016/j.jtbi.2010.08.019
15 https://doi.org/10.1016/s0959-4388(00)00261-0
16 https://doi.org/10.1086/344398
17 https://doi.org/10.1086/344780
18 https://doi.org/10.1086/377106
19 https://doi.org/10.1086/378099
20 https://doi.org/10.1093/bioinformatics/bth907
21 https://doi.org/10.1093/bioinformatics/btp236
22 https://doi.org/10.1093/hmg/9.16.2403
23 https://doi.org/10.1101/gr.1837404
24 https://doi.org/10.1101/gr.483802
25 https://doi.org/10.1126/science.1065573
26 https://doi.org/10.1126/science.1069424
27 https://doi.org/10.1145/1629175.1629198
28 https://doi.org/10.1159/000073729
29 schema:datePublished 2011
30 schema:datePublishedReg 2011-01-01
31 schema:description SNPs are fundamental roles for various applications including medical diagnostic, phylogenies and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Genetic variants that are near each other tend to be inherited together; these regions of linked variants are known as haplotypes. Recently, genetics researches revealed that SNPs within certain haplotype blocks induce only a few distinct common haplotypes in the majority of the population. The existence of haplotype block structure has serious implications for association-based methods for the mapping of disease genes. This paper proposes a parallel haplotype block partition and SNPs selection method under a diversity function by using the Hadoop MapReduce framework. The experiment shows that the proposed MapReduce-paralleled combinatorial algorithm performs well on the real-world data obtained in from the HapMap data set; the computation efficiency can be significantly improved proportional to the number of processors being used.
32 schema:editor N440b707929fe436bb3ec74720c14faea
33 schema:genre chapter
34 schema:inLanguage en
35 schema:isAccessibleForFree false
36 schema:isPartOf Nb7e3747d7bef42189d1066fb08ce5a5e
37 schema:name CloudTSS: A TagSNP Selection Approach on Cloud Computing
38 schema:pagination 525-534
39 schema:productId N0d7a0475f8964ae988afac7f203cb5b1
40 N8a009794aa634724b387b94d8aa9b6f1
41 Na8a9b1995bb14185a41fd0d993cd8cab
42 schema:publisher N4fb3a3fce51b4ea08fa76b9585786b7e
43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026543934
44 https://doi.org/10.1007/978-3-642-27180-9_64
45 schema:sdDatePublished 2019-04-15T20:10
46 schema:sdLicense https://scigraph.springernature.com/explorer/license/
47 schema:sdPublisher N799742e6f07940b38d5d76dae6e22408
48 schema:url http://link.springer.com/10.1007/978-3-642-27180-9_64
49 sgo:license sg:explorer/license/
50 sgo:sdDataset chapters
51 rdf:type schema:Chapter
52 N01ddf0c5081a4e67a2b3b3b8ecad75db rdf:first N46431af081ec4b779e49cceaf63f2caf
53 rdf:rest Nc8bd8a172fd84602b1de1d9565ba7a4b
54 N0d7a0475f8964ae988afac7f203cb5b1 schema:name dimensions_id
55 schema:value pub.1026543934
56 rdf:type schema:PropertyValue
57 N41cd93c50140419a8eb1718756441053 rdf:first Nb20861cd07394008afaa0d72e2e82c42
58 rdf:rest N01ddf0c5081a4e67a2b3b3b8ecad75db
59 N440b707929fe436bb3ec74720c14faea rdf:first Nfc9435df2d9247808c9ff7dc3113e6b1
60 rdf:rest Ned9678b841814bc291cc0ab92c81e87c
61 N46431af081ec4b779e49cceaf63f2caf schema:familyName Gervasi
62 schema:givenName Osvaldo
63 rdf:type schema:Person
64 N478a3b5e4a0c402b8f1754f00a15d3c0 rdf:first sg:person.01055745073.69
65 rdf:rest Nf77f1e7bac7242908fa2e9f929da4fc4
66 N4812b2d4e7784f759c05decfaa651951 schema:familyName Kang
67 schema:givenName Byeong-Ho
68 rdf:type schema:Person
69 N4fb3a3fce51b4ea08fa76b9585786b7e schema:location Berlin, Heidelberg
70 schema:name Springer Berlin Heidelberg
71 rdf:type schema:Organisation
72 N572dd6fe65364fe9ad90bc2e0f61db2f rdf:first sg:person.01336120166.62
73 rdf:rest Nc8ab1238caad4f56ae0919f8ac8a44b7
74 N6eae99c516fc4664ab498b5d03ec159e schema:familyName Adeli
75 schema:givenName Hojjat
76 rdf:type schema:Person
77 N799742e6f07940b38d5d76dae6e22408 schema:name Springer Nature - SN SciGraph project
78 rdf:type schema:Organization
79 N8a009794aa634724b387b94d8aa9b6f1 schema:name doi
80 schema:value 10.1007/978-3-642-27180-9_64
81 rdf:type schema:PropertyValue
82 N9a42430c117b47b180739d43b16c4767 rdf:first Na04c8b502e4c455daa54132a275b3ac5
83 rdf:rest rdf:nil
84 N9c1637bdb6d24f84a4137432878a69f6 rdf:first N4812b2d4e7784f759c05decfaa651951
85 rdf:rest N9a42430c117b47b180739d43b16c4767
86 Na04c8b502e4c455daa54132a275b3ac5 schema:familyName Villalba
87 schema:givenName Javier García
88 rdf:type schema:Person
89 Na8a9b1995bb14185a41fd0d993cd8cab schema:name readcube_id
90 schema:value 7e74d8372f6b2a1dd337c92b1fc4be9c693eb8266bf2350b7829eb29c404ba18
91 rdf:type schema:PropertyValue
92 Nb20861cd07394008afaa0d72e2e82c42 schema:familyName Cho
93 schema:givenName Hyun-seob
94 rdf:type schema:Person
95 Nb7e3747d7bef42189d1066fb08ce5a5e schema:isbn 978-3-642-27179-3
96 978-3-642-27180-9
97 schema:name Grid and Distributed Computing
98 rdf:type schema:Book
99 Nc6bd21aeb53845d38605a92ab8ac8130 schema:familyName Yau
100 schema:givenName Stephen S.
101 rdf:type schema:Person
102 Nc8ab1238caad4f56ae0919f8ac8a44b7 rdf:first sg:person.01032717740.48
103 rdf:rest N478a3b5e4a0c402b8f1754f00a15d3c0
104 Nc8bd8a172fd84602b1de1d9565ba7a4b rdf:first Nc6bd21aeb53845d38605a92ab8ac8130
105 rdf:rest N9c1637bdb6d24f84a4137432878a69f6
106 Ned9678b841814bc291cc0ab92c81e87c rdf:first N6eae99c516fc4664ab498b5d03ec159e
107 rdf:rest N41cd93c50140419a8eb1718756441053
108 Nf77f1e7bac7242908fa2e9f929da4fc4 rdf:first sg:person.012113441135.19
109 rdf:rest rdf:nil
110 Nfc9435df2d9247808c9ff7dc3113e6b1 schema:familyName Kim
111 schema:givenName Tai-hoon
112 rdf:type schema:Person
113 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
114 schema:name Biological Sciences
115 rdf:type schema:DefinedTerm
116 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
117 schema:name Genetics
118 rdf:type schema:DefinedTerm
119 sg:person.01032717740.48 schema:affiliation https://www.grid.ac/institutes/grid.412550.7
120 schema:familyName Lin
121 schema:givenName Yaw-Ling
122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01032717740.48
123 rdf:type schema:Person
124 sg:person.01055745073.69 schema:affiliation https://www.grid.ac/institutes/grid.412550.7
125 schema:familyName Hua
126 schema:givenName Guan-Jie
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01055745073.69
128 rdf:type schema:Person
129 sg:person.012113441135.19 schema:affiliation https://www.grid.ac/institutes/grid.412550.7
130 schema:familyName Hu
131 schema:givenName Yu-Chen
132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012113441135.19
133 rdf:type schema:Person
134 sg:person.01336120166.62 schema:affiliation https://www.grid.ac/institutes/grid.412550.7
135 schema:familyName Hung
136 schema:givenName Che-Lun
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01336120166.62
138 rdf:type schema:Person
139 sg:pub.10.1007/978-3-540-69733-6_31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047382730
140 https://doi.org/10.1007/978-3-540-69733-6_31
141 rdf:type schema:CreativeWork
142 sg:pub.10.1038/nature00864 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040675195
143 https://doi.org/10.1038/nature00864
144 rdf:type schema:CreativeWork
145 sg:pub.10.1038/ng1001-229 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026787741
146 https://doi.org/10.1038/ng1001-229
147 rdf:type schema:CreativeWork
148 sg:pub.10.1038/ng1001-233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017573512
149 https://doi.org/10.1038/ng1001-233
150 rdf:type schema:CreativeWork
151 sg:pub.10.1038/sj.mp.4001779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023011769
152 https://doi.org/10.1038/sj.mp.4001779
153 rdf:type schema:CreativeWork
154 sg:pub.10.1186/1471-2105-11-s12-s1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044778751
155 https://doi.org/10.1186/1471-2105-11-s12-s1
156 rdf:type schema:CreativeWork
157 sg:pub.10.1186/1471-2105-6-303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035277876
158 https://doi.org/10.1186/1471-2105-6-303
159 rdf:type schema:CreativeWork
160 https://app.dimensions.ai/details/publication/pub.1080090263 schema:CreativeWork
161 https://doi.org/10.1016/j.humimm.2005.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049231837
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/j.jbi.2010.05.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027321888
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.jtbi.2010.08.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029981129
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/s0959-4388(00)00261-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008356697
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1086/344398 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058640423
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1086/344780 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058640580
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1086/377106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058670200
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1086/378099 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058671155
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1093/bioinformatics/bth907 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005165631
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1093/bioinformatics/btp236 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029688589
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1093/hmg/9.16.2403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041769869
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1101/gr.1837404 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047213321
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1101/gr.483802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037792121
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1126/science.1065573 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062445519
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1126/science.1069424 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010139737
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1145/1629175.1629198 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006814493
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1159/000073729 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014435426
194 rdf:type schema:CreativeWork
195 https://www.grid.ac/institutes/grid.412550.7 schema:alternateName Providence University
196 schema:name Dept. of Computer Science & Communication Engineering, Providence University, 200 Chung Chi Rd., Taichung, 43301, Republic of China, Taiwan
197 Dept. of Computer Science & Information Management, Providence University, 200 Chung Chi Rd., Taichung, 43301, Republic of China, Taiwan
198 rdf:type schema:Organization
 




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


...