{"id":"https://openalex.org/W2116346453","doi":"https://doi.org/10.1109/cibcb.2009.4925737","title":"DDPIn - Distance and density based protein indexing","display_name":"DDPIn - Distance and density based protein indexing","publication_year":2009,"publication_date":"2009-03-01","ids":{"openalex":"https://openalex.org/W2116346453","doi":"https://doi.org/10.1109/cibcb.2009.4925737","mag":"2116346453"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb.2009.4925737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb.2009.4925737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","raw_type":"proceedings-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/A5049617942","display_name":"David Hoksza","orcid":"https://orcid.org/0000-0003-4679-0557"},"institutions":[{"id":"https://openalex.org/I21250087","display_name":"Charles University","ror":"https://ror.org/024d6js02","country_code":"CZ","type":"education","lineage":["https://openalex.org/I21250087"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"David Hoksza","raw_affiliation_strings":["Charles University, Prague, Czechia"],"affiliations":[{"raw_affiliation_string":"Charles University, Prague, Czechia","institution_ids":["https://openalex.org/I21250087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5049617942"],"corresponding_institution_ids":["https://openalex.org/I21250087"],"apc_list":null,"apc_paid":null,"fwci":0.5391,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6711119,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"5","issue":null,"first_page":"263","last_page":"270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9961000084877014,"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":0.9961000084877014,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9959999918937683,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/search-engine-indexing","display_name":"Search engine indexing","score":0.6838676929473877},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6699734926223755},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5526401400566101},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4914463758468628},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4823305308818817},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4540650248527527},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.44567349553108215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42799127101898193},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.42181533575057983},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4158875048160553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39498424530029297},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30239251255989075},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1803741157054901},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07285505533218384}],"concepts":[{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6838676929473877},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6699734926223755},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5526401400566101},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4914463758468628},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4823305308818817},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4540650248527527},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.44567349553108215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42799127101898193},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.42181533575057983},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4158875048160553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39498424530029297},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30239251255989075},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1803741157054901},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07285505533218384},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cibcb.2009.4925737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb.2009.4925737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.541.1044","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.541.1044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://siret.ms.mff.cuni.cz/hoksza/papers/cibcb2009_ddpin.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":22,"referenced_works":["https://openalex.org/W1979147581","https://openalex.org/W1979791990","https://openalex.org/W1992208183","https://openalex.org/W2022058405","https://openalex.org/W2050330741","https://openalex.org/W2053281575","https://openalex.org/W2056807348","https://openalex.org/W2085277871","https://openalex.org/W2087064593","https://openalex.org/W2097471670","https://openalex.org/W2102475449","https://openalex.org/W2108067237","https://openalex.org/W2108138353","https://openalex.org/W2117499714","https://openalex.org/W2118851904","https://openalex.org/W2133724340","https://openalex.org/W2136567909","https://openalex.org/W2144071905","https://openalex.org/W2152326664","https://openalex.org/W2157092487","https://openalex.org/W2161773631","https://openalex.org/W6682969285"],"related_works":["https://openalex.org/W3024364549","https://openalex.org/W4206019083","https://openalex.org/W1976265003","https://openalex.org/W2054476758","https://openalex.org/W2370378377","https://openalex.org/W2048865712","https://openalex.org/W4210535024","https://openalex.org/W4237510188","https://openalex.org/W2130160813","https://openalex.org/W841163430"],"abstract_inverted_index":{"Protein":[0],"structure":[1,27,40,105,109],"similarity":[2],"and":[3,13,32,127],"classification":[4,125,134],"methods":[5,88],"have":[6],"many":[7],"applications":[8],"in":[9],"protein":[10,26,39],"function":[11],"prediction":[12],"associated":[14],"fields":[15],"(e.g.":[16],"drug":[17],"discovery).":[18],"In":[19,35],"this":[20],"paper,":[21],"we":[22,85,115],"propose":[23],"a":[24,70,94,102],"new":[25],"representation":[28],"method":[29],"enabling":[30],"fast":[31],"accurate":[33],"classification.":[34],"our":[36,111],"approach,":[37],"each":[38,77],"is":[41,99,107],"represented":[42],"by":[43],"number":[44,55],"of":[45,50,56,78,110],"vectors":[46],"(based":[47],"on":[48],"histogram":[49],"distances)":[51],"equivalent":[52],"to":[53,76,89,130],"the":[54,74,79,108,131],"its":[57],"C":[58,64],"<sub":[59,65],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[60,66],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">alpha</sub>":[61,67],"residues.":[62],"Each":[63],"residue":[68],"represents":[69],"viewpoint":[71],"from":[72],"which":[73,98,121],"distances":[75,92],"other":[80],"residues":[81],"are":[82],"computed.":[83],"Consequently,":[84],"use":[86,116],"several":[87],"convert":[90],"these":[91],"into":[93],"n-dimensional":[95],"feature":[96],"vector":[97],"indexed":[100],"using":[101],"metric":[103],"indexing":[104],"(M-tree":[106],"choice).":[112],"While":[113],"searching,":[114],"single":[117],"or":[118],"multi-step":[119],"approach":[120],"provides":[122],"us":[123],"with":[124],"accuracy":[126],"speed":[128],"comparable":[129],"best":[132],"contemporary":[133],"methods.":[135]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
