Rapid and Accurate Protein Side Chain Prediction with Local Backbone Information View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2008

AUTHORS

Jing Zhang , Xin Gao , Jinbo Xu , Ming Li

ABSTRACT

High-accuracy protein structure modeling demands accurate and very fast side chain prediction since such a procedure must be repeatedly called at each step of structure refinement. Many known side chain prediction programs, such as SCWRL and TreePack, depend on the philosophy that global information and pairwise energy function must be used to achieve high accuracy. These programs are too slow to be used in the case when side chain packing has to be used thousands of times, such as protein structure refinement and protein design. We present an unexpected study that local backbone information can determine side chain conformations accurately. LocalPack, our side chain packing program which is based on only local information, achieves equal accuracy as SCWRL and TreePack, yet runs 4-14 times faster, hence providing a key missing piece in our efforts to high-accuracy protein structure modeling. More... »

PAGES

285-299

References to SciGraph publications

Book

TITLE

Research in Computational Molecular Biology

ISBN

978-3-540-78838-6
978-3-540-78839-3

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-78839-3_25

DOI

http://dx.doi.org/10.1007/978-3-540-78839-3_25

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018157563


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/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Tsinghua University", 
          "id": "https://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "David R. Cheriton School of Computer Science, University of Waterloo, N2L 6P7, Waterloo, Ontario, Canada", 
            "The Institute for Theoretical Computer Science, Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Jing", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Waterloo", 
          "id": "https://www.grid.ac/institutes/grid.46078.3d", 
          "name": [
            "David R. Cheriton School of Computer Science, University of Waterloo, N2L 6P7, Waterloo, Ontario, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gao", 
        "givenName": "Xin", 
        "id": "sg:person.0752774111.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752774111.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Toyota Technological Institute At Chicago", 
          "id": "https://www.grid.ac/institutes/grid.287491.1", 
          "name": [
            "Toyota Technological Institute at Chicago, 60637, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xu", 
        "givenName": "Jinbo", 
        "id": "sg:person.0603660076.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0603660076.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Waterloo", 
          "id": "https://www.grid.ac/institutes/grid.46078.3d", 
          "name": [
            "David R. Cheriton School of Computer Science, University of Waterloo, N2L 6P7, Waterloo, Ontario, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Ming", 
        "id": "sg:person.0621576316.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0621576316.79"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/pro.5560041006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000089401"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/356539a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000184640", 
          "https://doi.org/10.1038/356539a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/13.3.291", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000502198"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/1097-0282(200108)59:2<72::aid-bip1007>3.0.co;2-s", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001396968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1110/ps.062165906", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002507445"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmbi.1993.1172", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003964662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jcc.10420", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004673150"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(89)90109-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006701870"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.96.16.9074", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008289970"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1110/ps.03250104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008897002"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/3-540-44696-6_10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009326242", 
          "https://doi.org/10.1007/3-540-44696-6_10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1015330.1015341", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011745635"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmbi.2001.4865", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015749545"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(87)90358-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016209422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-71681-5_27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018269273", 
          "https://doi.org/10.1007/978-3-540-71681-5_27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmbi.1993.1170", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019589109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(78)90408-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023143486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(87)90314-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027348746"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nsb0594-334", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028819831", 
          "https://doi.org/10.1038/nsb0594-334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1096-987x(19961115)17:14<1667::aid-jcc8>3.0.co;2-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029987098"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1399-3011.1983.tb02062.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030150266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1399-3011.1983.tb02062.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030150266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmbi.1993.1626", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030443070"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1162349.1162350", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031054153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/bip.360360106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031226025"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/prot.10629", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031844765"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0022-2836(91)90550-p", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032275346"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0959-440x(02)00344-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032459601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0959-440x(02)00344-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032459601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1110/ps.24902", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032913835"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pro.5560050511", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034905759"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pro.5560050511", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034905759"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11415770_32", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035348483", 
          "https://doi.org/10.1007/11415770_32"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11415770_32", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035348483", 
          "https://doi.org/10.1007/11415770_32"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/protein/15.10.779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040299364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/prot.340140208", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042264709"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/prot.340140208", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042264709"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1359-0278(97)00006-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042709982"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pro.5560060807", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042933715"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1399-3011.1979.tb01866.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045546660"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1399-3011.1979.tb01866.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045546660"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/bti144", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047725318"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/07391102.1991.10507882", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050353771"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1110/ps.03154503", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050369828"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1399-3011.1970.tb01679.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053582644"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1399-3011.1970.tb01679.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053582644"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.461157", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058039168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/protein/8.4.363", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059981219"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1142/s0219720003000186", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063004510"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/ijoc.1040.0096", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064706513"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.7551/mitpress/4908.001.0001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110621625"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2008", 
    "datePublishedReg": "2008-01-01", 
    "description": "High-accuracy protein structure modeling demands accurate and very fast side chain prediction since such a procedure must be repeatedly called at each step of structure refinement. Many known side chain prediction programs, such as SCWRL and TreePack, depend on the philosophy that global information and pairwise energy function must be used to achieve high accuracy. These programs are too slow to be used in the case when side chain packing has to be used thousands of times, such as protein structure refinement and protein design. We present an unexpected study that local backbone information can determine side chain conformations accurately. LocalPack, our side chain packing program which is based on only local information, achieves equal accuracy as SCWRL and TreePack, yet runs 4-14 times faster, hence providing a key missing piece in our efforts to high-accuracy protein structure modeling.", 
    "editor": [
      {
        "familyName": "Vingron", 
        "givenName": "Martin", 
        "type": "Person"
      }, 
      {
        "familyName": "Wong", 
        "givenName": "Limsoon", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-540-78839-3_25", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-540-78838-6", 
        "978-3-540-78839-3"
      ], 
      "name": "Research in Computational Molecular Biology", 
      "type": "Book"
    }, 
    "name": "Rapid and Accurate Protein Side Chain Prediction with Local Backbone Information", 
    "pagination": "285-299", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-540-78839-3_25"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "5683ebae61cf77d7c93c70f9f3482212ce001d751221845be446e1ffccc118d0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1018157563"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-540-78839-3_25", 
      "https://app.dimensions.ai/details/publication/pub.1018157563"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T05:59", 
    "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/v90/0000000349_0000000349/records_113647_00000000.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-540-78839-3_25"
  }
]
 

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.10.1007/978-3-540-78839-3_25'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-78839-3_25'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-78839-3_25'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-78839-3_25'


 

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

234 TRIPLES      23 PREDICATES      71 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-540-78839-3_25 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N1be5d35c5b9d4844ae56d379bf7690de
4 schema:citation sg:pub.10.1007/11415770_32
5 sg:pub.10.1007/3-540-44696-6_10
6 sg:pub.10.1007/978-3-540-71681-5_27
7 sg:pub.10.1038/356539a0
8 sg:pub.10.1038/nsb0594-334
9 https://doi.org/10.1002/(sici)1096-987x(19961115)17:14<1667::aid-jcc8>3.0.co;2-j
10 https://doi.org/10.1002/1097-0282(200108)59:2<72::aid-bip1007>3.0.co;2-s
11 https://doi.org/10.1002/bip.360360106
12 https://doi.org/10.1002/jcc.10420
13 https://doi.org/10.1002/pro.5560041006
14 https://doi.org/10.1002/pro.5560050511
15 https://doi.org/10.1002/pro.5560060807
16 https://doi.org/10.1002/prot.10629
17 https://doi.org/10.1002/prot.340140208
18 https://doi.org/10.1006/jmbi.1993.1170
19 https://doi.org/10.1006/jmbi.1993.1172
20 https://doi.org/10.1006/jmbi.1993.1626
21 https://doi.org/10.1006/jmbi.2001.4865
22 https://doi.org/10.1016/0022-2836(78)90408-4
23 https://doi.org/10.1016/0022-2836(87)90314-7
24 https://doi.org/10.1016/0022-2836(87)90358-5
25 https://doi.org/10.1016/0022-2836(89)90109-5
26 https://doi.org/10.1016/0022-2836(91)90550-p
27 https://doi.org/10.1016/s0959-440x(02)00344-5
28 https://doi.org/10.1016/s1359-0278(97)00006-0
29 https://doi.org/10.1063/1.461157
30 https://doi.org/10.1073/pnas.96.16.9074
31 https://doi.org/10.1080/07391102.1991.10507882
32 https://doi.org/10.1093/bioinformatics/13.3.291
33 https://doi.org/10.1093/bioinformatics/bti144
34 https://doi.org/10.1093/protein/15.10.779
35 https://doi.org/10.1093/protein/8.4.363
36 https://doi.org/10.1110/ps.03154503
37 https://doi.org/10.1110/ps.03250104
38 https://doi.org/10.1110/ps.062165906
39 https://doi.org/10.1110/ps.24902
40 https://doi.org/10.1111/j.1399-3011.1970.tb01679.x
41 https://doi.org/10.1111/j.1399-3011.1979.tb01866.x
42 https://doi.org/10.1111/j.1399-3011.1983.tb02062.x
43 https://doi.org/10.1142/s0219720003000186
44 https://doi.org/10.1145/1015330.1015341
45 https://doi.org/10.1145/1162349.1162350
46 https://doi.org/10.1287/ijoc.1040.0096
47 https://doi.org/10.7551/mitpress/4908.001.0001
48 schema:datePublished 2008
49 schema:datePublishedReg 2008-01-01
50 schema:description High-accuracy protein structure modeling demands accurate and very fast side chain prediction since such a procedure must be repeatedly called at each step of structure refinement. Many known side chain prediction programs, such as SCWRL and TreePack, depend on the philosophy that global information and pairwise energy function must be used to achieve high accuracy. These programs are too slow to be used in the case when side chain packing has to be used thousands of times, such as protein structure refinement and protein design. We present an unexpected study that local backbone information can determine side chain conformations accurately. LocalPack, our side chain packing program which is based on only local information, achieves equal accuracy as SCWRL and TreePack, yet runs 4-14 times faster, hence providing a key missing piece in our efforts to high-accuracy protein structure modeling.
51 schema:editor Nb0703e90c0414752b3f6c78f298de0d6
52 schema:genre chapter
53 schema:inLanguage en
54 schema:isAccessibleForFree false
55 schema:isPartOf N7076e0fbc7b54003a456e85c55fe8363
56 schema:name Rapid and Accurate Protein Side Chain Prediction with Local Backbone Information
57 schema:pagination 285-299
58 schema:productId N0b88a11573c944e190bf8e99d24a09f2
59 N91ff77eaf9954a35b78fb3370ce91da0
60 Nb5b43687ea164a74866a4181c9917eff
61 schema:publisher N2c8a8936668c46c08378b54a31d452a4
62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018157563
63 https://doi.org/10.1007/978-3-540-78839-3_25
64 schema:sdDatePublished 2019-04-16T05:59
65 schema:sdLicense https://scigraph.springernature.com/explorer/license/
66 schema:sdPublisher N6d1d56a15d374f3c9acdf8dbc399ef76
67 schema:url https://link.springer.com/10.1007%2F978-3-540-78839-3_25
68 sgo:license sg:explorer/license/
69 sgo:sdDataset chapters
70 rdf:type schema:Chapter
71 N0b88a11573c944e190bf8e99d24a09f2 schema:name readcube_id
72 schema:value 5683ebae61cf77d7c93c70f9f3482212ce001d751221845be446e1ffccc118d0
73 rdf:type schema:PropertyValue
74 N1be5d35c5b9d4844ae56d379bf7690de rdf:first N676f8bb5f3c54a6283b9248f9c828d25
75 rdf:rest N7c3a7f37ed194c928274f9770de4fef3
76 N2c8a8936668c46c08378b54a31d452a4 schema:location Berlin, Heidelberg
77 schema:name Springer Berlin Heidelberg
78 rdf:type schema:Organisation
79 N5b438d4ac1994418b8632ecce2bf7e1a schema:familyName Wong
80 schema:givenName Limsoon
81 rdf:type schema:Person
82 N5c59df733e48486e971f69f7c06186d1 rdf:first sg:person.0621576316.79
83 rdf:rest rdf:nil
84 N676f8bb5f3c54a6283b9248f9c828d25 schema:affiliation https://www.grid.ac/institutes/grid.12527.33
85 schema:familyName Zhang
86 schema:givenName Jing
87 rdf:type schema:Person
88 N68c6f9a2cdc24cc786934fac1137baa3 rdf:first sg:person.0603660076.01
89 rdf:rest N5c59df733e48486e971f69f7c06186d1
90 N6d1d56a15d374f3c9acdf8dbc399ef76 schema:name Springer Nature - SN SciGraph project
91 rdf:type schema:Organization
92 N7076e0fbc7b54003a456e85c55fe8363 schema:isbn 978-3-540-78838-6
93 978-3-540-78839-3
94 schema:name Research in Computational Molecular Biology
95 rdf:type schema:Book
96 N7c3a7f37ed194c928274f9770de4fef3 rdf:first sg:person.0752774111.04
97 rdf:rest N68c6f9a2cdc24cc786934fac1137baa3
98 N91ff77eaf9954a35b78fb3370ce91da0 schema:name doi
99 schema:value 10.1007/978-3-540-78839-3_25
100 rdf:type schema:PropertyValue
101 Nb0703e90c0414752b3f6c78f298de0d6 rdf:first Ne1d458abf8b7422887888c9136753ccb
102 rdf:rest Nf0a6141963164bb2b3a9a1ae810b4991
103 Nb5b43687ea164a74866a4181c9917eff schema:name dimensions_id
104 schema:value pub.1018157563
105 rdf:type schema:PropertyValue
106 Ne1d458abf8b7422887888c9136753ccb schema:familyName Vingron
107 schema:givenName Martin
108 rdf:type schema:Person
109 Nf0a6141963164bb2b3a9a1ae810b4991 rdf:first N5b438d4ac1994418b8632ecce2bf7e1a
110 rdf:rest rdf:nil
111 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
112 schema:name Medical and Health Sciences
113 rdf:type schema:DefinedTerm
114 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
115 schema:name Clinical Sciences
116 rdf:type schema:DefinedTerm
117 sg:person.0603660076.01 schema:affiliation https://www.grid.ac/institutes/grid.287491.1
118 schema:familyName Xu
119 schema:givenName Jinbo
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0603660076.01
121 rdf:type schema:Person
122 sg:person.0621576316.79 schema:affiliation https://www.grid.ac/institutes/grid.46078.3d
123 schema:familyName Li
124 schema:givenName Ming
125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0621576316.79
126 rdf:type schema:Person
127 sg:person.0752774111.04 schema:affiliation https://www.grid.ac/institutes/grid.46078.3d
128 schema:familyName Gao
129 schema:givenName Xin
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752774111.04
131 rdf:type schema:Person
132 sg:pub.10.1007/11415770_32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035348483
133 https://doi.org/10.1007/11415770_32
134 rdf:type schema:CreativeWork
135 sg:pub.10.1007/3-540-44696-6_10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009326242
136 https://doi.org/10.1007/3-540-44696-6_10
137 rdf:type schema:CreativeWork
138 sg:pub.10.1007/978-3-540-71681-5_27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018269273
139 https://doi.org/10.1007/978-3-540-71681-5_27
140 rdf:type schema:CreativeWork
141 sg:pub.10.1038/356539a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000184640
142 https://doi.org/10.1038/356539a0
143 rdf:type schema:CreativeWork
144 sg:pub.10.1038/nsb0594-334 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028819831
145 https://doi.org/10.1038/nsb0594-334
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1002/(sici)1096-987x(19961115)17:14<1667::aid-jcc8>3.0.co;2-j schema:sameAs https://app.dimensions.ai/details/publication/pub.1029987098
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1002/1097-0282(200108)59:2<72::aid-bip1007>3.0.co;2-s schema:sameAs https://app.dimensions.ai/details/publication/pub.1001396968
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1002/bip.360360106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031226025
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1002/jcc.10420 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004673150
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1002/pro.5560041006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000089401
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1002/pro.5560050511 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034905759
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1002/pro.5560060807 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042933715
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1002/prot.10629 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031844765
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1002/prot.340140208 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042264709
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1006/jmbi.1993.1170 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019589109
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1006/jmbi.1993.1172 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003964662
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1006/jmbi.1993.1626 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030443070
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1006/jmbi.2001.4865 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015749545
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/0022-2836(78)90408-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023143486
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/0022-2836(87)90314-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027348746
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/0022-2836(87)90358-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016209422
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/0022-2836(89)90109-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006701870
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/0022-2836(91)90550-p schema:sameAs https://app.dimensions.ai/details/publication/pub.1032275346
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1016/s0959-440x(02)00344-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032459601
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1016/s1359-0278(97)00006-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042709982
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1063/1.461157 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058039168
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1073/pnas.96.16.9074 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008289970
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1080/07391102.1991.10507882 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050353771
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1093/bioinformatics/13.3.291 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000502198
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1093/bioinformatics/bti144 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047725318
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1093/protein/15.10.779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040299364
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1093/protein/8.4.363 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059981219
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1110/ps.03154503 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050369828
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1110/ps.03250104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008897002
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1110/ps.062165906 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002507445
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1110/ps.24902 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032913835
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1111/j.1399-3011.1970.tb01679.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1053582644
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1111/j.1399-3011.1979.tb01866.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1045546660
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1111/j.1399-3011.1983.tb02062.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1030150266
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1142/s0219720003000186 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063004510
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1145/1015330.1015341 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011745635
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1145/1162349.1162350 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031054153
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1287/ijoc.1040.0096 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064706513
222 rdf:type schema:CreativeWork
223 https://doi.org/10.7551/mitpress/4908.001.0001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110621625
224 rdf:type schema:CreativeWork
225 https://www.grid.ac/institutes/grid.12527.33 schema:alternateName Tsinghua University
226 schema:name David R. Cheriton School of Computer Science, University of Waterloo, N2L 6P7, Waterloo, Ontario, Canada
227 The Institute for Theoretical Computer Science, Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China
228 rdf:type schema:Organization
229 https://www.grid.ac/institutes/grid.287491.1 schema:alternateName Toyota Technological Institute At Chicago
230 schema:name Toyota Technological Institute at Chicago, 60637, Chicago, IL, USA
231 rdf:type schema:Organization
232 https://www.grid.ac/institutes/grid.46078.3d schema:alternateName University of Waterloo
233 schema:name David R. Cheriton School of Computer Science, University of Waterloo, N2L 6P7, Waterloo, Ontario, Canada
234 rdf:type schema:Organization
 




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


...