The fidelity of annealing-ligation: A theoretical analysis View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2001-04-25

AUTHORS

John A. Rose , Russell J. Deaton

ABSTRACT

Understanding the nature of the error propagation through successive biosteps is critical to modeling the overall fidelity of computational DNA architectures. In this work, the fidelity of the compound biostep annealing-ligation is discussed in the limit of zero dissociation, within the framework of a simple statistical thermodynamic model. For simplicity, a DNA ligase of ideal infidelity is assumed, with its error behavior taken as bounding that of real DNA ligases. The derived expression for the fidelity of annealing-ligation indicates that the error coupling is both strong and dependent on sequence. Estimates of the fidelities of annealing and annealing-ligation have also been calculated for various encodings of Adleman’s graph, assuming a staggered zipper model of duplex formation. Results indicate the necessity of including information regarding the specific free energies and/or occupancies of accessible duplex states, in addition to information based purely on sequence comparison. More... »

PAGES

231-246

Book

TITLE

DNA Computing

ISBN

978-3-540-42076-7
978-3-540-44992-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-44992-2_16

DOI

http://dx.doi.org/10.1007/3-540-44992-2_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021365181


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": "University of Tokyo", 
          "id": "https://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Institute of Physics, The University of Tokyo, Komaba 3-8-1, 153, Meguro-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rose", 
        "givenName": "John A.", 
        "id": "sg:person.01070343251.68", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01070343251.68"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Arkansas at Fayetteville", 
          "id": "https://www.grid.ac/institutes/grid.411017.2", 
          "name": [
            "Department of Computer Science and Computer Engineering, The University of Arkansas, 72701, Fayetteville, Ark, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Deaton", 
        "givenName": "Russell J.", 
        "id": "sg:person.0707334604.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707334604.60"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1093/nar/24.15.3071", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005412787"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/26.22.5203", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008213040"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0303-2647(99)00045-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010665684"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0076-6879(92)11004-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016411947"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/289203a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016700249", 
          "https://doi.org/10.1038/289203a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(72)90170-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023253729"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0921-8777(97)00050-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029278758"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/21.10.2287", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029576767"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/25.17.3403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031011728"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0921-8777(90)90011-s", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032434506"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.bi.60.070191.002401", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033709474"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/15.19.7831", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040873429"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-1119(89)90165-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041302096"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-1119(89)90165-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041302096"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/15.21.8755", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042078734"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/26.18.4259", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042508950"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.186.4166.790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046248225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(88)90248-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049276331"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.88.1.189", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050067650"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0076-6879(79)68006-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052778808"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi00049a029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055158795"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi00162a013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055163284"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi00453a038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055176885"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi962590c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055213079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi962590c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055213079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi9916372", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055218333"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/bi9916372", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055218333"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.80.417", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060817430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.80.417", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060817430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.3413476", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062613076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.7973651", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062650775"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/dimacs/027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1097022560"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/dimacs/044", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1097022682"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2001-04-25", 
    "datePublishedReg": "2001-04-25", 
    "description": "Understanding the nature of the error propagation through successive biosteps is critical to modeling the overall fidelity of computational DNA architectures. In this work, the fidelity of the compound biostep annealing-ligation is discussed in the limit of zero dissociation, within the framework of a simple statistical thermodynamic model. For simplicity, a DNA ligase of ideal infidelity is assumed, with its error behavior taken as bounding that of real DNA ligases. The derived expression for the fidelity of annealing-ligation indicates that the error coupling is both strong and dependent on sequence. Estimates of the fidelities of annealing and annealing-ligation have also been calculated for various encodings of Adleman\u2019s graph, assuming a staggered zipper model of duplex formation. Results indicate the necessity of including information regarding the specific free energies and/or occupancies of accessible duplex states, in addition to information based purely on sequence comparison.", 
    "editor": [
      {
        "familyName": "Condon", 
        "givenName": "Anne", 
        "type": "Person"
      }, 
      {
        "familyName": "Rozenberg", 
        "givenName": "Grzegorz", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/3-540-44992-2_16", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-540-42076-7", 
        "978-3-540-44992-8"
      ], 
      "name": "DNA Computing", 
      "type": "Book"
    }, 
    "name": "The fidelity of annealing-ligation: A theoretical analysis", 
    "pagination": "231-246", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/3-540-44992-2_16"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "65cb2845158d8c3f44a3963ae37d04735dd255f42bebe813acb9e6f478b45110"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1021365181"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/3-540-44992-2_16", 
      "https://app.dimensions.ai/details/publication/pub.1021365181"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T05:31", 
    "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/v90/0000000346_0000000346/records_99809_00000001.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F3-540-44992-2_16"
  }
]
 

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.10.1007/3-540-44992-2_16'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/3-540-44992-2_16'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/3-540-44992-2_16'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/3-540-44992-2_16'


 

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

168 TRIPLES      23 PREDICATES      55 URIs      19 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/3-540-44992-2_16 schema:about anzsrc-for:06
2 anzsrc-for:0604
3 schema:author N2a4ccd32449d4190b5ee9f2a3bb0d38d
4 schema:citation sg:pub.10.1038/289203a0
5 https://doi.org/10.1016/0022-2836(72)90170-2
6 https://doi.org/10.1016/0022-2836(88)90248-3
7 https://doi.org/10.1016/0076-6879(79)68006-0
8 https://doi.org/10.1016/0076-6879(92)11004-3
9 https://doi.org/10.1016/0378-1119(89)90165-0
10 https://doi.org/10.1016/0921-8777(90)90011-s
11 https://doi.org/10.1016/s0303-2647(99)00045-3
12 https://doi.org/10.1016/s0921-8777(97)00050-5
13 https://doi.org/10.1021/bi00049a029
14 https://doi.org/10.1021/bi00162a013
15 https://doi.org/10.1021/bi00453a038
16 https://doi.org/10.1021/bi962590c
17 https://doi.org/10.1021/bi9916372
18 https://doi.org/10.1073/pnas.88.1.189
19 https://doi.org/10.1090/dimacs/027
20 https://doi.org/10.1090/dimacs/044
21 https://doi.org/10.1093/nar/15.19.7831
22 https://doi.org/10.1093/nar/15.21.8755
23 https://doi.org/10.1093/nar/21.10.2287
24 https://doi.org/10.1093/nar/24.15.3071
25 https://doi.org/10.1093/nar/25.17.3403
26 https://doi.org/10.1093/nar/26.18.4259
27 https://doi.org/10.1093/nar/26.22.5203
28 https://doi.org/10.1103/physrevlett.80.417
29 https://doi.org/10.1126/science.186.4166.790
30 https://doi.org/10.1126/science.3413476
31 https://doi.org/10.1126/science.7973651
32 https://doi.org/10.1146/annurev.bi.60.070191.002401
33 schema:datePublished 2001-04-25
34 schema:datePublishedReg 2001-04-25
35 schema:description Understanding the nature of the error propagation through successive biosteps is critical to modeling the overall fidelity of computational DNA architectures. In this work, the fidelity of the compound biostep annealing-ligation is discussed in the limit of zero dissociation, within the framework of a simple statistical thermodynamic model. For simplicity, a DNA ligase of ideal infidelity is assumed, with its error behavior taken as bounding that of real DNA ligases. The derived expression for the fidelity of annealing-ligation indicates that the error coupling is both strong and dependent on sequence. Estimates of the fidelities of annealing and annealing-ligation have also been calculated for various encodings of Adleman’s graph, assuming a staggered zipper model of duplex formation. Results indicate the necessity of including information regarding the specific free energies and/or occupancies of accessible duplex states, in addition to information based purely on sequence comparison.
36 schema:editor N1558c1a2323e471abeb154c8a29e27a6
37 schema:genre chapter
38 schema:inLanguage en
39 schema:isAccessibleForFree false
40 schema:isPartOf N8ceb052900f442a8b1b3e8487439214d
41 schema:name The fidelity of annealing-ligation: A theoretical analysis
42 schema:pagination 231-246
43 schema:productId N74bd24ca72d240d0b83ea8db2a27d0dd
44 N8c963e394da746f2aa625769bb49da53
45 Nbf1e3f2dd6d24d2c870293e91f22f1fe
46 schema:publisher Nc877f77f27e044ae811bc7c8f58a1659
47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021365181
48 https://doi.org/10.1007/3-540-44992-2_16
49 schema:sdDatePublished 2019-04-16T05:31
50 schema:sdLicense https://scigraph.springernature.com/explorer/license/
51 schema:sdPublisher N420dbf7cf63449b695a1794277547b14
52 schema:url https://link.springer.com/10.1007%2F3-540-44992-2_16
53 sgo:license sg:explorer/license/
54 sgo:sdDataset chapters
55 rdf:type schema:Chapter
56 N028e32c41efe44aabcbdeff887ef50fa schema:familyName Rozenberg
57 schema:givenName Grzegorz
58 rdf:type schema:Person
59 N1558c1a2323e471abeb154c8a29e27a6 rdf:first Nc6f3a687a4e542cd96ce111b333df875
60 rdf:rest N76b1423986a649d49c1dc7ba1957c785
61 N2a4ccd32449d4190b5ee9f2a3bb0d38d rdf:first sg:person.01070343251.68
62 rdf:rest Ndd042e44b4cc416aa41a483d6812401c
63 N420dbf7cf63449b695a1794277547b14 schema:name Springer Nature - SN SciGraph project
64 rdf:type schema:Organization
65 N74bd24ca72d240d0b83ea8db2a27d0dd schema:name doi
66 schema:value 10.1007/3-540-44992-2_16
67 rdf:type schema:PropertyValue
68 N76b1423986a649d49c1dc7ba1957c785 rdf:first N028e32c41efe44aabcbdeff887ef50fa
69 rdf:rest rdf:nil
70 N8c963e394da746f2aa625769bb49da53 schema:name readcube_id
71 schema:value 65cb2845158d8c3f44a3963ae37d04735dd255f42bebe813acb9e6f478b45110
72 rdf:type schema:PropertyValue
73 N8ceb052900f442a8b1b3e8487439214d schema:isbn 978-3-540-42076-7
74 978-3-540-44992-8
75 schema:name DNA Computing
76 rdf:type schema:Book
77 Nbf1e3f2dd6d24d2c870293e91f22f1fe schema:name dimensions_id
78 schema:value pub.1021365181
79 rdf:type schema:PropertyValue
80 Nc6f3a687a4e542cd96ce111b333df875 schema:familyName Condon
81 schema:givenName Anne
82 rdf:type schema:Person
83 Nc877f77f27e044ae811bc7c8f58a1659 schema:location Berlin, Heidelberg
84 schema:name Springer Berlin Heidelberg
85 rdf:type schema:Organisation
86 Ndd042e44b4cc416aa41a483d6812401c rdf:first sg:person.0707334604.60
87 rdf:rest rdf:nil
88 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
89 schema:name Biological Sciences
90 rdf:type schema:DefinedTerm
91 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
92 schema:name Genetics
93 rdf:type schema:DefinedTerm
94 sg:person.01070343251.68 schema:affiliation https://www.grid.ac/institutes/grid.26999.3d
95 schema:familyName Rose
96 schema:givenName John A.
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01070343251.68
98 rdf:type schema:Person
99 sg:person.0707334604.60 schema:affiliation https://www.grid.ac/institutes/grid.411017.2
100 schema:familyName Deaton
101 schema:givenName Russell J.
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707334604.60
103 rdf:type schema:Person
104 sg:pub.10.1038/289203a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016700249
105 https://doi.org/10.1038/289203a0
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1016/0022-2836(72)90170-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023253729
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1016/0022-2836(88)90248-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049276331
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/0076-6879(79)68006-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052778808
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/0076-6879(92)11004-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016411947
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/0378-1119(89)90165-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041302096
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/0921-8777(90)90011-s schema:sameAs https://app.dimensions.ai/details/publication/pub.1032434506
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/s0303-2647(99)00045-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010665684
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/s0921-8777(97)00050-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029278758
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1021/bi00049a029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055158795
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1021/bi00162a013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055163284
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1021/bi00453a038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055176885
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1021/bi962590c schema:sameAs https://app.dimensions.ai/details/publication/pub.1055213079
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1021/bi9916372 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055218333
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1073/pnas.88.1.189 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050067650
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1090/dimacs/027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1097022560
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1090/dimacs/044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1097022682
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1093/nar/15.19.7831 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040873429
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1093/nar/15.21.8755 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042078734
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1093/nar/21.10.2287 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029576767
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1093/nar/24.15.3071 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005412787
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1093/nar/25.17.3403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031011728
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1093/nar/26.18.4259 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042508950
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1093/nar/26.22.5203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008213040
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1103/physrevlett.80.417 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060817430
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1126/science.186.4166.790 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046248225
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1126/science.3413476 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062613076
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1126/science.7973651 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062650775
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1146/annurev.bi.60.070191.002401 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033709474
162 rdf:type schema:CreativeWork
163 https://www.grid.ac/institutes/grid.26999.3d schema:alternateName University of Tokyo
164 schema:name Institute of Physics, The University of Tokyo, Komaba 3-8-1, 153, Meguro-ku, Tokyo, Japan
165 rdf:type schema:Organization
166 https://www.grid.ac/institutes/grid.411017.2 schema:alternateName University of Arkansas at Fayetteville
167 schema:name Department of Computer Science and Computer Engineering, The University of Arkansas, 72701, Fayetteville, Ark, USA
168 rdf:type schema:Organization
 




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


...