A fast tool for minimum hybridization networks View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-07-02

AUTHORS

Zhi-Zhong Chen, Lusheng Wang, Satoshi Yamanaka

ABSTRACT

BackgroundDue to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to combine the two phylogenetic trees into a hybridization network with the fewest hybridization events. This leads to three computational problems, namely, the problem of computing the minimum size of a hybridization network, the problem of constructing one minimum hybridization network, and the problem of enumerating a representative set of minimum hybridization networks. The previously best software tools for these problems (namely, Chen and Wang’s HybridNet and Albrecht et al.’s Dendroscope 3) run very slowly for large instances that cannot be reduced to relatively small instances. Indeed, when the minimum size of a hybridization network of two given trees is larger than 23 and the problem for the trees cannot be reduced to relatively smaller independent subproblems, then HybridNet almost always takes longer than 1 day and Dendroscope 3 often fails to complete. Thus, a faster software tool for the problems is in need.ResultsWe develop a software tool in ANSI C, named FastHN, for the following problems: Computing the minimum size of a hybridization network, constructing one minimum hybridization network, and enumerating a representative set of minimum hybridization networks. We obtain FastHN by refining HybridNet with three ideas. The first idea is to preprocess the input trees so that the trees become smaller or the problem becomes to solve two or more relatively smaller independent subproblems. The second idea is to use a fast algorithm for computing the rSPR distance of two given phylognetic trees to cut more branches of the search tree in the exhaustive-search stage of the algorithm. The third idea is that during the exhaustive-search stage of the algorithm, we find two sibling leaves in one of the two forests (obtained from the given trees by cutting some edges) such that they are as far as possible in the other forest. As the result, FastHN always runs much faster than HybridNet. Unlike Dendroscope 3, FastHN is a single-threaded program. Despite this disadvantage, our experimental data shows that FastHN runs substantially faster than the multi-threaded Dendroscope 3 on a PC with multiple cores. Indeed, FastHN can finish within 16 minutes (on average on a Windows-7 (x64) desktop PC with i7-2600 CPU) even if the minimum size of a hybridization network of two given trees is about 25, the trees each have 100 leaves, and the problem for the input trees cannot be reduced to two or more independent subproblems via cluster reductions. It is also worth mentioning that like HybridNet, FastHN does not use much memory (indeed, the amount of memory is at most quadratic in the input size). In contrast, Dendroscope 3 uses a huge amount of memory. Executables of FastHN for Windows XP (x86), Windows 7 (x64), Linux, and Mac OS are available (see the Results and discussion section for details).ConclusionsFor both biological datasets and simulated datasets, our experimental results show that FastHN runs substantially faster than HybridNet and Dendroscope 3. The superiority of FastHN in speed over the previous tools becomes more significant as the hybridization number becomes larger. In addition, FastHN uses much less memory than Dendroscope 3 and uses the same amount of memory as HybridNet. More... »

PAGES

155

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2105-13-155

DOI

http://dx.doi.org/10.1186/1471-2105-13-155

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1013236358

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22748099


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0802", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Computation Theory and Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Algorithms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computational Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computer Simulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hybridization, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phylogeny", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Poaceae", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Software", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Division of Information System Design, Tokyo Denki University, Ishizaka, Hatoyama, 359-0394, Hiki, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412773.4", 
          "name": [
            "Division of Information System Design, Tokyo Denki University, Ishizaka, Hatoyama, 359-0394, Hiki, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chen", 
        "givenName": "Zhi-Zhong", 
        "id": "sg:person.015654265661.98", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015654265661.98"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong", 
          "id": "http://www.grid.ac/institutes/grid.35030.35", 
          "name": [
            "Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Lusheng", 
        "id": "sg:person.01105113721.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01105113721.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Information System Design, Tokyo Denki University, Ishizaka, Hatoyama, 359-0394, Hiki, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.412773.4", 
          "name": [
            "Division of Information System Design, Tokyo Denki University, Ishizaka, Hatoyama, 359-0394, Hiki, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamanaka", 
        "givenName": "Satoshi", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00285-005-0315-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004690562", 
          "https://doi.org/10.1007/s00285-005-0315-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-13078-6_23", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026208880", 
          "https://doi.org/10.1007/978-3-642-13078-6_23"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2148-10-42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017964138", 
          "https://doi.org/10.1186/1471-2148-10-42"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2148-6-15", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031420454", 
          "https://doi.org/10.1186/1471-2148-6-15"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00026-004-0229-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049592483", 
          "https://doi.org/10.1007/s00026-004-0229-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-9-532", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020382975", 
          "https://doi.org/10.1186/1471-2105-9-532"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-13193-6_13", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021203456", 
          "https://doi.org/10.1007/978-3-642-13193-6_13"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-8-460", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050692349", 
          "https://doi.org/10.1186/1471-2105-8-460"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012-07-02", 
    "datePublishedReg": "2012-07-02", 
    "description": "BackgroundDue to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to combine the two phylogenetic trees into a hybridization network with the fewest hybridization events. This leads to three computational problems, namely, the problem of computing the minimum size of a hybridization network, the problem of constructing one minimum hybridization network, and the problem of enumerating a representative set of minimum hybridization networks. The previously best software tools for these problems (namely, Chen and Wang\u2019s HybridNet and Albrecht et al.\u2019s Dendroscope 3) run very slowly for large instances that cannot be reduced to relatively small instances. Indeed, when the minimum size of a hybridization network of two given trees is larger than 23 and the problem for the trees cannot be reduced to relatively smaller independent subproblems, then HybridNet almost always takes longer than 1 day and Dendroscope 3 often fails to complete. Thus, a faster software tool for the problems is in need.ResultsWe develop a software tool in ANSI C, named FastHN, for the following problems: Computing the minimum size of a hybridization network, constructing one minimum hybridization network, and enumerating a representative set of minimum hybridization networks. We obtain FastHN by refining HybridNet with three ideas. The first idea is to preprocess the input trees so that the trees become smaller or the problem becomes to solve two or more relatively smaller independent subproblems. The second idea is to use a fast algorithm for computing the rSPR distance of two given phylognetic trees to cut more branches of the search tree in the exhaustive-search stage of the algorithm. The third idea is that during the exhaustive-search stage of the algorithm, we find two sibling leaves in one of the two forests (obtained from the given trees by cutting some edges) such that they are as far as possible in the other forest. As the result, FastHN always runs much faster than HybridNet. Unlike Dendroscope 3, FastHN is a single-threaded program. Despite this disadvantage, our experimental data shows that FastHN runs substantially faster than the multi-threaded Dendroscope 3 on a PC with multiple cores. Indeed, FastHN can finish within 16 minutes (on average on a Windows-7 (x64) desktop PC with i7-2600 CPU) even if the minimum size of a hybridization network of two given trees is about 25, the trees each have 100 leaves, and the problem for the input trees cannot be reduced to two or more independent subproblems via cluster reductions. It is also worth mentioning that like HybridNet, FastHN does not use much memory (indeed, the amount of memory is at most quadratic in the input size). In contrast, Dendroscope 3 uses a huge amount of memory. Executables of FastHN for Windows XP (x86), Windows 7 (x64), Linux, and Mac OS are available (see the Results and discussion section for details).ConclusionsFor both biological datasets and simulated datasets, our experimental results show that FastHN runs substantially faster than HybridNet and Dendroscope 3. The superiority of FastHN in speed over the previous tools becomes more significant as the hybridization number becomes larger. In addition, FastHN uses much less memory than Dendroscope 3 and uses the same amount of memory as HybridNet.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/1471-2105-13-155", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6078852", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.7427614", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1023786", 
        "issn": [
          "1471-2105"
        ], 
        "name": "BMC Bioinformatics", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "13"
      }
    ], 
    "keywords": [
      "minimum hybridization networks", 
      "software tools", 
      "smaller independent subproblems", 
      "independent subproblems", 
      "hybridization networks", 
      "better software tools", 
      "input trees", 
      "ANSI C", 
      "fast software tool", 
      "Mac OS", 
      "Windows XP", 
      "search tree", 
      "Windows 7", 
      "representative set", 
      "hybridization number", 
      "less memory", 
      "computational problems", 
      "small instances", 
      "multiple cores", 
      "large instances", 
      "HybridNet", 
      "huge amount", 
      "set of species", 
      "biological datasets", 
      "fast algorithm", 
      "previous tools", 
      "rSPR distance", 
      "network", 
      "phylogenetic tree", 
      "algorithm", 
      "subproblems", 
      "hybridization events", 
      "experimental results", 
      "second idea", 
      "dataset", 
      "first idea", 
      "different phylogenetic trees", 
      "minimum size", 
      "set", 
      "fast tool", 
      "tool", 
      "Linux", 
      "executables", 
      "memory", 
      "trees", 
      "different genes", 
      "instances", 
      "experimental data show", 
      "idea", 
      "third idea", 
      "problem", 
      "PC", 
      "leaves", 
      "species", 
      "data show", 
      "XP", 
      "superiority", 
      "forest", 
      "more branches", 
      "genes", 
      "speed", 
      "OS", 
      "amount", 
      "disadvantages", 
      "need", 
      "results", 
      "show", 
      "size", 
      "number", 
      "stage", 
      "distance", 
      "program", 
      "evolution", 
      "core", 
      "branches", 
      "events", 
      "same amount", 
      "cluster reduction", 
      "cases", 
      "contrast", 
      "addition", 
      "ResultsWe", 
      "reduction", 
      "days", 
      "minutes", 
      "BackgroundDue", 
      "ConclusionsFor"
    ], 
    "name": "A fast tool for minimum hybridization networks", 
    "pagination": "155", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1013236358"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2105-13-155"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22748099"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2105-13-155", 
      "https://app.dimensions.ai/details/publication/pub.1013236358"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-05-20T07:27", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_571.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/1471-2105-13-155"
  }
]
 

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.10.1186/1471-2105-13-155'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-13-155'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-13-155'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-13-155'


 

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

232 TRIPLES      22 PREDICATES      129 URIs      112 LITERALS      14 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2105-13-155 schema:about N1b54ba4c7db4459c89a7a5b0bdff72ec
2 N1bbd19e0d9034375822be288323d2510
3 N2b86809fd71d444aa2045503ea5a8a12
4 N2f8fbceb39dd4a5081b8dc7bdbb21400
5 N4e17343418fe442083b5b82333e9fd90
6 N7c7d2adc8d65486d9e1818d0b5b165b6
7 Nd265cbf240f84c3ca935f8c5c80003a6
8 anzsrc-for:08
9 anzsrc-for:0802
10 anzsrc-for:0806
11 schema:author N9caa4a55bc2b4b6abe8db0fdc04a93d9
12 schema:citation sg:pub.10.1007/978-3-642-13078-6_23
13 sg:pub.10.1007/978-3-642-13193-6_13
14 sg:pub.10.1007/s00026-004-0229-z
15 sg:pub.10.1007/s00285-005-0315-9
16 sg:pub.10.1186/1471-2105-8-460
17 sg:pub.10.1186/1471-2105-9-532
18 sg:pub.10.1186/1471-2148-10-42
19 sg:pub.10.1186/1471-2148-6-15
20 schema:datePublished 2012-07-02
21 schema:datePublishedReg 2012-07-02
22 schema:description BackgroundDue to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to combine the two phylogenetic trees into a hybridization network with the fewest hybridization events. This leads to three computational problems, namely, the problem of computing the minimum size of a hybridization network, the problem of constructing one minimum hybridization network, and the problem of enumerating a representative set of minimum hybridization networks. The previously best software tools for these problems (namely, Chen and Wang’s HybridNet and Albrecht et al.’s Dendroscope 3) run very slowly for large instances that cannot be reduced to relatively small instances. Indeed, when the minimum size of a hybridization network of two given trees is larger than 23 and the problem for the trees cannot be reduced to relatively smaller independent subproblems, then HybridNet almost always takes longer than 1 day and Dendroscope 3 often fails to complete. Thus, a faster software tool for the problems is in need.ResultsWe develop a software tool in ANSI C, named FastHN, for the following problems: Computing the minimum size of a hybridization network, constructing one minimum hybridization network, and enumerating a representative set of minimum hybridization networks. We obtain FastHN by refining HybridNet with three ideas. The first idea is to preprocess the input trees so that the trees become smaller or the problem becomes to solve two or more relatively smaller independent subproblems. The second idea is to use a fast algorithm for computing the rSPR distance of two given phylognetic trees to cut more branches of the search tree in the exhaustive-search stage of the algorithm. The third idea is that during the exhaustive-search stage of the algorithm, we find two sibling leaves in one of the two forests (obtained from the given trees by cutting some edges) such that they are as far as possible in the other forest. As the result, FastHN always runs much faster than HybridNet. Unlike Dendroscope 3, FastHN is a single-threaded program. Despite this disadvantage, our experimental data shows that FastHN runs substantially faster than the multi-threaded Dendroscope 3 on a PC with multiple cores. Indeed, FastHN can finish within 16 minutes (on average on a Windows-7 (x64) desktop PC with i7-2600 CPU) even if the minimum size of a hybridization network of two given trees is about 25, the trees each have 100 leaves, and the problem for the input trees cannot be reduced to two or more independent subproblems via cluster reductions. It is also worth mentioning that like HybridNet, FastHN does not use much memory (indeed, the amount of memory is at most quadratic in the input size). In contrast, Dendroscope 3 uses a huge amount of memory. Executables of FastHN for Windows XP (x86), Windows 7 (x64), Linux, and Mac OS are available (see the Results and discussion section for details).ConclusionsFor both biological datasets and simulated datasets, our experimental results show that FastHN runs substantially faster than HybridNet and Dendroscope 3. The superiority of FastHN in speed over the previous tools becomes more significant as the hybridization number becomes larger. In addition, FastHN uses much less memory than Dendroscope 3 and uses the same amount of memory as HybridNet.
23 schema:genre article
24 schema:inLanguage en
25 schema:isAccessibleForFree true
26 schema:isPartOf N123e67874f23475e968512cea0ad34b0
27 N7109d0825b214003a7f8edacd2f86072
28 sg:journal.1023786
29 schema:keywords ANSI C
30 BackgroundDue
31 ConclusionsFor
32 HybridNet
33 Linux
34 Mac OS
35 OS
36 PC
37 ResultsWe
38 Windows 7
39 Windows XP
40 XP
41 addition
42 algorithm
43 amount
44 better software tools
45 biological datasets
46 branches
47 cases
48 cluster reduction
49 computational problems
50 contrast
51 core
52 data show
53 dataset
54 days
55 different genes
56 different phylogenetic trees
57 disadvantages
58 distance
59 events
60 evolution
61 executables
62 experimental data show
63 experimental results
64 fast algorithm
65 fast software tool
66 fast tool
67 first idea
68 forest
69 genes
70 huge amount
71 hybridization events
72 hybridization networks
73 hybridization number
74 idea
75 independent subproblems
76 input trees
77 instances
78 large instances
79 leaves
80 less memory
81 memory
82 minimum hybridization networks
83 minimum size
84 minutes
85 more branches
86 multiple cores
87 need
88 network
89 number
90 phylogenetic tree
91 previous tools
92 problem
93 program
94 rSPR distance
95 reduction
96 representative set
97 results
98 same amount
99 search tree
100 second idea
101 set
102 set of species
103 show
104 size
105 small instances
106 smaller independent subproblems
107 software tools
108 species
109 speed
110 stage
111 subproblems
112 superiority
113 third idea
114 tool
115 trees
116 schema:name A fast tool for minimum hybridization networks
117 schema:pagination 155
118 schema:productId N077b419707ac4ce1a92602d7dae20f57
119 Nc6e0d58151574f2e858d30bfc1192f92
120 Ndcec0e82b5644d4fb2a2f0ea2735bb8e
121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013236358
122 https://doi.org/10.1186/1471-2105-13-155
123 schema:sdDatePublished 2022-05-20T07:27
124 schema:sdLicense https://scigraph.springernature.com/explorer/license/
125 schema:sdPublisher N64d6bd81028043e8a959a6c70f953bbf
126 schema:url https://doi.org/10.1186/1471-2105-13-155
127 sgo:license sg:explorer/license/
128 sgo:sdDataset articles
129 rdf:type schema:ScholarlyArticle
130 N077b419707ac4ce1a92602d7dae20f57 schema:name doi
131 schema:value 10.1186/1471-2105-13-155
132 rdf:type schema:PropertyValue
133 N123e67874f23475e968512cea0ad34b0 schema:volumeNumber 13
134 rdf:type schema:PublicationVolume
135 N1b54ba4c7db4459c89a7a5b0bdff72ec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Software
137 rdf:type schema:DefinedTerm
138 N1bbd19e0d9034375822be288323d2510 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Phylogeny
140 rdf:type schema:DefinedTerm
141 N2b86809fd71d444aa2045503ea5a8a12 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Computer Simulation
143 rdf:type schema:DefinedTerm
144 N2bdd1211e9df4ac793d97f0475d30562 schema:affiliation grid-institutes:grid.412773.4
145 schema:familyName Yamanaka
146 schema:givenName Satoshi
147 rdf:type schema:Person
148 N2f8fbceb39dd4a5081b8dc7bdbb21400 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
149 schema:name Poaceae
150 rdf:type schema:DefinedTerm
151 N38d63d30fb2741aca2ffe1389a18b3e3 rdf:first N2bdd1211e9df4ac793d97f0475d30562
152 rdf:rest rdf:nil
153 N4e17343418fe442083b5b82333e9fd90 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
154 schema:name Algorithms
155 rdf:type schema:DefinedTerm
156 N64d6bd81028043e8a959a6c70f953bbf schema:name Springer Nature - SN SciGraph project
157 rdf:type schema:Organization
158 N7109d0825b214003a7f8edacd2f86072 schema:issueNumber 1
159 rdf:type schema:PublicationIssue
160 N7c7d2adc8d65486d9e1818d0b5b165b6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
161 schema:name Hybridization, Genetic
162 rdf:type schema:DefinedTerm
163 N9caa4a55bc2b4b6abe8db0fdc04a93d9 rdf:first sg:person.015654265661.98
164 rdf:rest Nc5c9c9fcb1624178ac883a3d9813b153
165 Nc5c9c9fcb1624178ac883a3d9813b153 rdf:first sg:person.01105113721.52
166 rdf:rest N38d63d30fb2741aca2ffe1389a18b3e3
167 Nc6e0d58151574f2e858d30bfc1192f92 schema:name pubmed_id
168 schema:value 22748099
169 rdf:type schema:PropertyValue
170 Nd265cbf240f84c3ca935f8c5c80003a6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
171 schema:name Computational Biology
172 rdf:type schema:DefinedTerm
173 Ndcec0e82b5644d4fb2a2f0ea2735bb8e schema:name dimensions_id
174 schema:value pub.1013236358
175 rdf:type schema:PropertyValue
176 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
177 schema:name Information and Computing Sciences
178 rdf:type schema:DefinedTerm
179 anzsrc-for:0802 schema:inDefinedTermSet anzsrc-for:
180 schema:name Computation Theory and Mathematics
181 rdf:type schema:DefinedTerm
182 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
183 schema:name Information Systems
184 rdf:type schema:DefinedTerm
185 sg:grant.6078852 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2105-13-155
186 rdf:type schema:MonetaryGrant
187 sg:grant.7427614 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2105-13-155
188 rdf:type schema:MonetaryGrant
189 sg:journal.1023786 schema:issn 1471-2105
190 schema:name BMC Bioinformatics
191 schema:publisher Springer Nature
192 rdf:type schema:Periodical
193 sg:person.01105113721.52 schema:affiliation grid-institutes:grid.35030.35
194 schema:familyName Wang
195 schema:givenName Lusheng
196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01105113721.52
197 rdf:type schema:Person
198 sg:person.015654265661.98 schema:affiliation grid-institutes:grid.412773.4
199 schema:familyName Chen
200 schema:givenName Zhi-Zhong
201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015654265661.98
202 rdf:type schema:Person
203 sg:pub.10.1007/978-3-642-13078-6_23 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026208880
204 https://doi.org/10.1007/978-3-642-13078-6_23
205 rdf:type schema:CreativeWork
206 sg:pub.10.1007/978-3-642-13193-6_13 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021203456
207 https://doi.org/10.1007/978-3-642-13193-6_13
208 rdf:type schema:CreativeWork
209 sg:pub.10.1007/s00026-004-0229-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1049592483
210 https://doi.org/10.1007/s00026-004-0229-z
211 rdf:type schema:CreativeWork
212 sg:pub.10.1007/s00285-005-0315-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004690562
213 https://doi.org/10.1007/s00285-005-0315-9
214 rdf:type schema:CreativeWork
215 sg:pub.10.1186/1471-2105-8-460 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050692349
216 https://doi.org/10.1186/1471-2105-8-460
217 rdf:type schema:CreativeWork
218 sg:pub.10.1186/1471-2105-9-532 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020382975
219 https://doi.org/10.1186/1471-2105-9-532
220 rdf:type schema:CreativeWork
221 sg:pub.10.1186/1471-2148-10-42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017964138
222 https://doi.org/10.1186/1471-2148-10-42
223 rdf:type schema:CreativeWork
224 sg:pub.10.1186/1471-2148-6-15 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031420454
225 https://doi.org/10.1186/1471-2148-6-15
226 rdf:type schema:CreativeWork
227 grid-institutes:grid.35030.35 schema:alternateName Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong
228 schema:name Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong
229 rdf:type schema:Organization
230 grid-institutes:grid.412773.4 schema:alternateName Division of Information System Design, Tokyo Denki University, Ishizaka, Hatoyama, 359-0394, Hiki, Saitama, Japan
231 schema:name Division of Information System Design, Tokyo Denki University, Ishizaka, Hatoyama, 359-0394, Hiki, Saitama, Japan
232 rdf:type schema:Organization
 




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


...