{"id":"https://openalex.org/W2786733983","doi":"https://doi.org/10.1109/la-cci.2017.8285695","title":"Clustering algorithms applied on analysis of protein molecular dynamics","display_name":"Clustering algorithms applied on analysis of protein molecular dynamics","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2786733983","doi":"https://doi.org/10.1109/la-cci.2017.8285695","mag":"2786733983"},"language":"en","primary_location":{"id":"doi:10.1109/la-cci.2017.8285695","is_oa":false,"landing_page_url":"https://doi.org/10.1109/la-cci.2017.8285695","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","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/A5103185925","display_name":"Vin\u00edcius Carius de Souza","orcid":"https://orcid.org/0000-0001-8075-3253"},"institutions":[{"id":"https://openalex.org/I4210088805","display_name":"Hospital Universit\u00e1rio - Universidade Federal de Juiz de Fora","ror":"https://ror.org/0039g6563","country_code":"BR","type":"healthcare","lineage":["https://openalex.org/I4210088805"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Vinicius Carius de Souza","raw_affiliation_strings":["Federal University of Juiz de Fora, Minas Gerais, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Juiz de Fora, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I4210088805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004862221","display_name":"Leonardo Goliatt","orcid":"https://orcid.org/0000-0002-2844-9470"},"institutions":[{"id":"https://openalex.org/I4210088805","display_name":"Hospital Universit\u00e1rio - Universidade Federal de Juiz de Fora","ror":"https://ror.org/0039g6563","country_code":"BR","type":"healthcare","lineage":["https://openalex.org/I4210088805"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Leonardo Goliatt","raw_affiliation_strings":["Federal University of Juiz de Fora, Minas Gerais, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Juiz de Fora, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I4210088805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039718466","display_name":"Priscila Vanessa Zabala Capriles Goliatt","orcid":"https://orcid.org/0000-0001-9780-4328"},"institutions":[{"id":"https://openalex.org/I101100930","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44","country_code":"BR","type":"education","lineage":["https://openalex.org/I101100930"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Priscila V. Z. Capriles Goliatt","raw_affiliation_strings":["Universidade Federal de Juiz de Fora, Juiz de Fora, MG, BR"],"affiliations":[{"raw_affiliation_string":"Universidade Federal de Juiz de Fora, Juiz de Fora, MG, BR","institution_ids":["https://openalex.org/I101100930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103185925"],"corresponding_institution_ids":["https://openalex.org/I4210088805"],"apc_list":null,"apc_paid":null,"fwci":0.319,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.59505005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9984999895095825,"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":0.9984999895095825,"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/T11162","display_name":"Enzyme Structure and Function","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9794999957084656,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8454785346984863},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6420274972915649},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5966828465461731},{"id":"https://openalex.org/keywords/isomap","display_name":"Isomap","score":0.5906823873519897},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5476989150047302},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5098901987075806},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4298505187034607},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4168376922607422},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4014996588230133},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.31669196486473083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.267704576253891},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24447977542877197}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8454785346984863},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6420274972915649},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5966828465461731},{"id":"https://openalex.org/C2778626561","wikidata":"https://www.wikidata.org/wiki/Q6086067","display_name":"Isomap","level":4,"score":0.5906823873519897},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5476989150047302},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5098901987075806},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4298505187034607},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4168376922607422},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4014996588230133},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.31669196486473083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.267704576253891},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24447977542877197},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/la-cci.2017.8285695","is_oa":false,"landing_page_url":"https://doi.org/10.1109/la-cci.2017.8285695","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324372","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W163225181","https://openalex.org/W1653739410","https://openalex.org/W1898843043","https://openalex.org/W1986009775","https://openalex.org/W1989004357","https://openalex.org/W2014375183","https://openalex.org/W2016381774","https://openalex.org/W2025296083","https://openalex.org/W2067191022","https://openalex.org/W2071777829","https://openalex.org/W2071794983","https://openalex.org/W2083952632","https://openalex.org/W2093221728","https://openalex.org/W2122932522","https://openalex.org/W2162171655","https://openalex.org/W2163915395","https://openalex.org/W2165232124","https://openalex.org/W2332712348","https://openalex.org/W2964036159","https://openalex.org/W3013880646","https://openalex.org/W6606659748"],"related_works":["https://openalex.org/W2375574759","https://openalex.org/W1489327846","https://openalex.org/W4287375746","https://openalex.org/W3124275785","https://openalex.org/W2037225398","https://openalex.org/W2132734978","https://openalex.org/W2148415967","https://openalex.org/W2367590741","https://openalex.org/W2166963679","https://openalex.org/W1966347620"],"abstract_inverted_index":{"Analysis":[0],"of":[1,15,33,50,70],"molecular":[2],"dynamic":[3],"(MD)":[4],"simulation":[5],"has":[6],"been":[7,21],"difficult":[8],"since":[9],"this":[10,44],"method":[11],"generates":[12],"a":[13,41,93],"lot":[14],"conformations.":[16],"Thus":[17],"clustering":[18,61,79,100],"algorithms":[19,80],"have":[20],"applied":[22],"to":[23,36,60,96],"group":[24],"similar":[25],"structures":[26],"from":[27,55,102],"MD":[28],"simulations,":[29],"but":[30],"the":[31,34,48,111,131],"choice":[32],"information":[35,95],"be":[37,92,97],"clustered":[38],"is":[39],"still":[40],"challenge.":[42],"In":[43],"work,":[45],"we":[46],"propose":[47],"use":[49],"Euclidean":[51],"distance":[52],"matrices":[53],"(EDM)":[54],"conformations":[56,101],"as":[57],"input":[58],"data":[59,71,105,125,138],"algorithms.":[62],"We":[63],"used":[64,98],"approaches":[65],"combining":[66],"non-reduction":[67],"or":[68],"reduction":[69],"dimensionality":[72],"(MDS":[73],"and":[74,77,84,120,140],"isomap":[75],"methods),":[76],"different":[78],"(k-means,":[81],"ward,":[82],"mean-shift":[83,112],"affinity":[85],"propagation).":[86],"Results":[87],"indicated":[88],"that":[89,133],"EDM":[90],"could":[91],"good":[94,115,143],"in":[99,117],"MD.":[103],"For":[104],"with":[106,126,136],"small":[107],"protein":[108,128],"structure":[109,129],"variation,":[110,130],"algorithm":[113],"had":[114,142],"results":[116],"both":[118],"non-reduced":[119],"reduced":[121],"data.":[122],"However,":[123],"for":[124],"large":[127],"methods":[132],"work":[134],"better":[135],"smooth-density":[137],"(k-means":[139],"ward)":[141],"results.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-01-08T20:05:33.558190","created_date":"2025-10-10T00:00:00"}