Minimizing recombinations in consensus networks for phylogeographic studies View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-01

AUTHORS

Laxmi Parida, Asif Javed, Marta Melé, Francesc Calafell, Jaume Bertranpetit, Genographic Consortium

ABSTRACT

BACKGROUND: We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks G1 and G2, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network G3 with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within = sz(G1, G2) (function sz is a well-behaved function of the sizes and topologies of G1 and G2) of the optimal number of recombinations. To date, this is the best known result for a network consensus problem. RESULTS: Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations. CONCLUSION: We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology. More... »

PAGES

s72

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2105-10-s1-s72

DOI

http://dx.doi.org/10.1186/1471-2105-10-s1-s72

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021721164

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19208177


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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Africa", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Algorithms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chromosome Mapping", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Chromosomes, Human, X", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Regulatory Networks", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genetics, Population", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phylogeny", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Recombination, Genetic", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "Computational Biology Center, IBM T J Watson Research, Yorktown, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Parida", 
        "givenName": "Laxmi", 
        "id": "sg:person.01336557015.68", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01336557015.68"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "IBM Research \u2013 Thomas J. Watson Research Center", 
          "id": "https://www.grid.ac/institutes/grid.481554.9", 
          "name": [
            "Department of Computer Science, Rensselaer Polytechnic Institute, New York, USA", 
            "Work done during an internship at IBM T J Watson Research Center, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Javed", 
        "givenName": "Asif", 
        "id": "sg:person.01034550504.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01034550504.38"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "IBM Research \u2013 Thomas J. Watson Research Center", 
          "id": "https://www.grid.ac/institutes/grid.481554.9", 
          "name": [
            "Biologia Evolutiva, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain", 
            "Work done during an internship at IBM T J Watson Research Center, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mel\u00e9", 
        "givenName": "Marta", 
        "id": "sg:person.011526330120.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011526330120.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Pompeu Fabra University", 
          "id": "https://www.grid.ac/institutes/grid.5612.0", 
          "name": [
            "Biologia Evolutiva, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Calafell", 
        "givenName": "Francesc", 
        "id": "sg:person.01036367335.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01036367335.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Pompeu Fabra University", 
          "id": "https://www.grid.ac/institutes/grid.5612.0", 
          "name": [
            "Biologia Evolutiva, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bertranpetit", 
        "givenName": "Jaume", 
        "id": "sg:person.0604654434.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0604654434.69"
        ], 
        "type": "Person"
      }, 
      {
        "familyName": "Genographic Consortium", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.dam.2005.05.044", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002168213"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1089/cmb.2008.0065", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059245685"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcbb.2004.10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061540427"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcbb.2004.44", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061540442"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2411550", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069920189"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2009-01", 
    "datePublishedReg": "2009-01-01", 
    "description": "BACKGROUND: We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks G1 and G2, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network G3 with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within = sz(G1, G2) (function sz is a well-behaved function of the sizes and topologies of G1 and G2) of the optimal number of recombinations. To date, this is the best known result for a network consensus problem.\nRESULTS: Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations.\nCONCLUSION: We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1471-2105-10-s1-s72", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1023786", 
        "issn": [
          "1471-2105"
        ], 
        "name": "BMC Bioinformatics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "Suppl 1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "10"
      }
    ], 
    "name": "Minimizing recombinations in consensus networks for phylogeographic studies", 
    "pagination": "s72", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "677d09d86971438c6ff808b6e25a47cf2624d9640df33c6fdce3818fbb7359c4"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "19208177"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100965194"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1471-2105-10-s1-s72"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1021721164"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1471-2105-10-s1-s72", 
      "https://app.dimensions.ai/details/publication/pub.1021721164"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T14:59", 
    "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_8663_00000505.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186/1471-2105-10-S1-S72"
  }
]
 

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.10.1186/1471-2105-10-s1-s72'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-10-s1-s72'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-10-s1-s72'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2105-10-s1-s72'


 

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

162 TRIPLES      21 PREDICATES      44 URIs      31 LITERALS      19 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1471-2105-10-s1-s72 schema:about N3c6a9ed314554e8680bbc9251d8fe53b
2 N68163deff547408797dbdf70a2dfb3ff
3 N80f11d8011af40eaae72127c12f91f30
4 Na8476a0df8ae4754b16a012b2f8c959a
5 Nae852f7444dd485493e2cc5ab4c4c42c
6 Nbf2bd343812b48ca98f8036a66ed7888
7 Nd02085e4249b4ff28082024697b6f98c
8 Ndacd4cbf9132489a954dd57faf102745
9 Ne822806f3c794fb2b1cc2aea1997c808
10 Nf89293b0b1634f2fa9af2a3ae8ed922f
11 anzsrc-for:06
12 anzsrc-for:0604
13 schema:author N7004f6ca13e143e38b523f2f7c16bbd8
14 schema:citation https://doi.org/10.1016/j.dam.2005.05.044
15 https://doi.org/10.1089/cmb.2008.0065
16 https://doi.org/10.1109/tcbb.2004.10
17 https://doi.org/10.1109/tcbb.2004.44
18 https://doi.org/10.2307/2411550
19 schema:datePublished 2009-01
20 schema:datePublishedReg 2009-01-01
21 schema:description BACKGROUND: We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks G1 and G2, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network G3 with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within = sz(G1, G2) (function sz is a well-behaved function of the sizes and topologies of G1 and G2) of the optimal number of recombinations. To date, this is the best known result for a network consensus problem. RESULTS: Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations. CONCLUSION: We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology.
22 schema:genre research_article
23 schema:inLanguage en
24 schema:isAccessibleForFree true
25 schema:isPartOf N358bd9acfa5b4f08aef7122bbc4ef265
26 Na77a8ee0756847f7a698d94cf6a2ae44
27 sg:journal.1023786
28 schema:name Minimizing recombinations in consensus networks for phylogeographic studies
29 schema:pagination s72
30 schema:productId N7dd879d9c4714fd19b3c6475a31b36bb
31 N7ef539d84da3414dbf57c1ac274d6ab1
32 N99fee5de51564864aa922e8038f5407d
33 Nb8bccd5220cd4c4c900079c3b762f691
34 Nc90e18607a2246a2b64c3851e765e820
35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021721164
36 https://doi.org/10.1186/1471-2105-10-s1-s72
37 schema:sdDatePublished 2019-04-10T14:59
38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
39 schema:sdPublisher Nbe41b7f4d706462fb42369103dafaa5c
40 schema:url http://link.springer.com/10.1186/1471-2105-10-S1-S72
41 sgo:license sg:explorer/license/
42 sgo:sdDataset articles
43 rdf:type schema:ScholarlyArticle
44 N0e45e97ead36460e8a67dcf6e6c94782 schema:familyName Genographic Consortium
45 rdf:type schema:Person
46 N110f911d9ff64bd8934daf77c5edae10 rdf:first N0e45e97ead36460e8a67dcf6e6c94782
47 rdf:rest rdf:nil
48 N1f8ed4cd307044c79581ac321ae56640 rdf:first sg:person.011526330120.45
49 rdf:rest Nb69217a06a404165847235643f261a42
50 N358bd9acfa5b4f08aef7122bbc4ef265 schema:issueNumber Suppl 1
51 rdf:type schema:PublicationIssue
52 N3c6a9ed314554e8680bbc9251d8fe53b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
53 schema:name Recombination, Genetic
54 rdf:type schema:DefinedTerm
55 N68163deff547408797dbdf70a2dfb3ff schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
56 schema:name Gene Regulatory Networks
57 rdf:type schema:DefinedTerm
58 N7004f6ca13e143e38b523f2f7c16bbd8 rdf:first sg:person.01336557015.68
59 rdf:rest Nbe37e8314acc4068a79a7bcde1c1e863
60 N7d5e5e6f6aa64a1e9d4d7bf022b03e1a schema:name Computational Biology Center, IBM T J Watson Research, Yorktown, USA
61 rdf:type schema:Organization
62 N7dd879d9c4714fd19b3c6475a31b36bb schema:name dimensions_id
63 schema:value pub.1021721164
64 rdf:type schema:PropertyValue
65 N7ef539d84da3414dbf57c1ac274d6ab1 schema:name pubmed_id
66 schema:value 19208177
67 rdf:type schema:PropertyValue
68 N80f11d8011af40eaae72127c12f91f30 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
69 schema:name Genetics, Population
70 rdf:type schema:DefinedTerm
71 N99fee5de51564864aa922e8038f5407d schema:name doi
72 schema:value 10.1186/1471-2105-10-s1-s72
73 rdf:type schema:PropertyValue
74 Na77a8ee0756847f7a698d94cf6a2ae44 schema:volumeNumber 10
75 rdf:type schema:PublicationVolume
76 Na8476a0df8ae4754b16a012b2f8c959a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
77 schema:name Chromosomes, Human, X
78 rdf:type schema:DefinedTerm
79 Nabd03a09b44a47da8757d4608fb88c66 rdf:first sg:person.0604654434.69
80 rdf:rest N110f911d9ff64bd8934daf77c5edae10
81 Nae852f7444dd485493e2cc5ab4c4c42c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
82 schema:name Chromosome Mapping
83 rdf:type schema:DefinedTerm
84 Nb69217a06a404165847235643f261a42 rdf:first sg:person.01036367335.40
85 rdf:rest Nabd03a09b44a47da8757d4608fb88c66
86 Nb8bccd5220cd4c4c900079c3b762f691 schema:name nlm_unique_id
87 schema:value 100965194
88 rdf:type schema:PropertyValue
89 Nbe37e8314acc4068a79a7bcde1c1e863 rdf:first sg:person.01034550504.38
90 rdf:rest N1f8ed4cd307044c79581ac321ae56640
91 Nbe41b7f4d706462fb42369103dafaa5c schema:name Springer Nature - SN SciGraph project
92 rdf:type schema:Organization
93 Nbf2bd343812b48ca98f8036a66ed7888 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
94 schema:name Models, Genetic
95 rdf:type schema:DefinedTerm
96 Nc90e18607a2246a2b64c3851e765e820 schema:name readcube_id
97 schema:value 677d09d86971438c6ff808b6e25a47cf2624d9640df33c6fdce3818fbb7359c4
98 rdf:type schema:PropertyValue
99 Nd02085e4249b4ff28082024697b6f98c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Phylogeny
101 rdf:type schema:DefinedTerm
102 Ndacd4cbf9132489a954dd57faf102745 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
103 schema:name Africa
104 rdf:type schema:DefinedTerm
105 Ne822806f3c794fb2b1cc2aea1997c808 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
106 schema:name Algorithms
107 rdf:type schema:DefinedTerm
108 Nf89293b0b1634f2fa9af2a3ae8ed922f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Humans
110 rdf:type schema:DefinedTerm
111 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
112 schema:name Biological Sciences
113 rdf:type schema:DefinedTerm
114 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
115 schema:name Genetics
116 rdf:type schema:DefinedTerm
117 sg:journal.1023786 schema:issn 1471-2105
118 schema:name BMC Bioinformatics
119 rdf:type schema:Periodical
120 sg:person.01034550504.38 schema:affiliation https://www.grid.ac/institutes/grid.481554.9
121 schema:familyName Javed
122 schema:givenName Asif
123 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01034550504.38
124 rdf:type schema:Person
125 sg:person.01036367335.40 schema:affiliation https://www.grid.ac/institutes/grid.5612.0
126 schema:familyName Calafell
127 schema:givenName Francesc
128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01036367335.40
129 rdf:type schema:Person
130 sg:person.011526330120.45 schema:affiliation https://www.grid.ac/institutes/grid.481554.9
131 schema:familyName Melé
132 schema:givenName Marta
133 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011526330120.45
134 rdf:type schema:Person
135 sg:person.01336557015.68 schema:affiliation N7d5e5e6f6aa64a1e9d4d7bf022b03e1a
136 schema:familyName Parida
137 schema:givenName Laxmi
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01336557015.68
139 rdf:type schema:Person
140 sg:person.0604654434.69 schema:affiliation https://www.grid.ac/institutes/grid.5612.0
141 schema:familyName Bertranpetit
142 schema:givenName Jaume
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0604654434.69
144 rdf:type schema:Person
145 https://doi.org/10.1016/j.dam.2005.05.044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002168213
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1089/cmb.2008.0065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059245685
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1109/tcbb.2004.10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061540427
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1109/tcbb.2004.44 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061540442
152 rdf:type schema:CreativeWork
153 https://doi.org/10.2307/2411550 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069920189
154 rdf:type schema:CreativeWork
155 https://www.grid.ac/institutes/grid.481554.9 schema:alternateName IBM Research – Thomas J. Watson Research Center
156 schema:name Biologia Evolutiva, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
157 Department of Computer Science, Rensselaer Polytechnic Institute, New York, USA
158 Work done during an internship at IBM T J Watson Research Center, USA
159 rdf:type schema:Organization
160 https://www.grid.ac/institutes/grid.5612.0 schema:alternateName Pompeu Fabra University
161 schema:name Biologia Evolutiva, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
162 rdf:type schema:Organization
 




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


...