{"id":"https://openalex.org/W2068891361","doi":"https://doi.org/10.1137/05062754x","title":"A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation","display_name":"A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2068891361","doi":"https://doi.org/10.1137/05062754x","mag":"2068891361"},"language":"en","primary_location":{"id":"doi:10.1137/05062754x","is_oa":false,"landing_page_url":"https://doi.org/10.1137/05062754x","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101421618","display_name":"Pratik K. Biswas","orcid":"https://orcid.org/0000-0001-8570-3108"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pratik Biswas","raw_affiliation_strings":["pbiswas@stanford.edu#TAB#"],"affiliations":[{"raw_affiliation_string":"pbiswas@stanford.edu#TAB#","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064083862","display_name":"Kim-Chuan Toh","orcid":"https://orcid.org/0000-0001-7204-8933"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim-Chuan Toh","raw_affiliation_strings":["mattohkc@nus.edu.sg#TAB#"],"affiliations":[{"raw_affiliation_string":"mattohkc@nus.edu.sg#TAB#","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041526408","display_name":"Yinyu Ye","orcid":"https://orcid.org/0009-0001-3239-2622"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yinyu Ye","raw_affiliation_strings":["yinyu-ye@stanford.edu#TAB#"],"affiliations":[{"raw_affiliation_string":"yinyu-ye@stanford.edu#TAB#","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101421618"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8721,"has_fulltext":false,"cited_by_count":103,"citation_normalized_percentile":{"value":0.94027697,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"30","issue":"3","first_page":"1251","last_page":"1277"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9711999893188477,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.52321457862854},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5151833295822144},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4711873531341553},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.4335947632789612},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.37856388092041016},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37494534254074097}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.52321457862854},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5151833295822144},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4711873531341553},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.4335947632789612},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.37856388092041016},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37494534254074097},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1137/05062754x","is_oa":false,"landing_page_url":"https://doi.org/10.1137/05062754x","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Scientific Computing","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/102634","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/102634","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.62.5485","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.5485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.math.nus.edu.sg/~mattohkc/papers/distmolecule8.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W54695997","https://openalex.org/W90562166","https://openalex.org/W153025749","https://openalex.org/W167332904","https://openalex.org/W1482298744","https://openalex.org/W1489434708","https://openalex.org/W1490549637","https://openalex.org/W1577844362","https://openalex.org/W1582520000","https://openalex.org/W1585892185","https://openalex.org/W1595132914","https://openalex.org/W1873910681","https://openalex.org/W1967073510","https://openalex.org/W2001449111","https://openalex.org/W2014339452","https://openalex.org/W2015642465","https://openalex.org/W2017588182","https://openalex.org/W2049444669","https://openalex.org/W2050897335","https://openalex.org/W2057691786","https://openalex.org/W2061607408","https://openalex.org/W2066459185","https://openalex.org/W2075893026","https://openalex.org/W2077776048","https://openalex.org/W2078512044","https://openalex.org/W2087190244","https://openalex.org/W2092162155","https://openalex.org/W2093590551","https://openalex.org/W2095172966","https://openalex.org/W2110543129","https://openalex.org/W2118655515","https://openalex.org/W2125947724","https://openalex.org/W2130479394","https://openalex.org/W2143075842","https://openalex.org/W2145896324","https://openalex.org/W2146281661","https://openalex.org/W2152299057","https://openalex.org/W2156865565","https://openalex.org/W2176446742","https://openalex.org/W2186315365","https://openalex.org/W2481406420","https://openalex.org/W2913650195","https://openalex.org/W3138835833","https://openalex.org/W3210839039","https://openalex.org/W4240501996"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2562400057","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4360593462","https://openalex.org/W2194570607","https://openalex.org/W2807634898","https://openalex.org/W2793211469"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,51,66,85,111,151],"distributed":[3,36],"algorithm":[4,68,136],"for":[5],"solving":[6],"Euclidean":[7],"metric":[8],"realization":[9],"problems":[10],"arising":[11],"from":[12,130,150,172],"large":[13,147],"3-D":[14,104],"graphs,":[15],"using":[16,46],"only":[17],"noisy":[18],"distance":[19,169],"information":[20],"and":[21,55,78,142],"without":[22,160],"any":[23,30],"prior":[24],"knowledge":[25,163],"of":[26,29,31,81,101,107,114,146,154],"the":[27,32,38,79,99,103,131,144,166],"positions":[28,80],"vertices.":[33],"In":[34,92],"our":[35,96],"algorithm,":[37],"graph":[39],"is":[40,69,137],"first":[41],"subdivided":[42],"into":[43],"smaller":[44],"subgraphs":[45],"intelligent":[47],"clustering":[48],"methods.":[49],"Then":[50],"semidefinite":[52],"programming":[53],"relaxation":[54],"gradient":[56],"search":[57],"method":[58,97],"are":[59,89,128],"used":[60,70],"to":[61,71,98,139],"localize":[62],"each":[63],"subgraph.":[64],"Finally,":[65],"stitching":[67],"find":[72],"affine":[73],"maps":[74],"between":[75,118],"adjacent":[76],"clusters,":[77],"all":[82,123],"points":[83],"in":[84],"global":[86],"coordinate":[87],"system":[88],"then":[90],"derived.":[91],"particular,":[93],"we":[94],"apply":[95],"problem":[100],"finding":[102],"molecular":[105,126],"configurations":[106,145],"proteins":[108],"based":[109],"on":[110],"limited":[112,152],"number":[113,153],"given":[115],"pairwise":[116,155],"distances":[117,156],"atoms.":[119],"The":[120],"protein":[121,148],"molecules,":[122],"with":[124],"known":[125],"configurations,":[127],"taken":[129],"Protein":[132],"Data":[133],"Bank.":[134],"Our":[135],"able":[138],"reconstruct":[140],"reliably":[141],"efficiently":[143],"molecules":[149],"corrupted":[157],"by":[158],"noise,":[159],"incorporating":[161],"domain":[162],"such":[164],"as":[165],"minimum":[167],"separation":[168],"constraints":[170],"derived":[171],"van":[173],"der":[174],"Waals":[175],"interactions.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":13}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
