{"id":"https://openalex.org/W86438764","doi":null,"title":"Clustering and Registration of Functional Data with Applications in Time Course Genomics Data","display_name":"Clustering and Registration of Functional Data with Applications in Time Course Genomics Data","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W86438764","mag":"86438764"},"language":"en","primary_location":{"id":"pmh:oai:escholarship.org/ark:/13030/qt0d01t79f","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/0d01t79f","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"etd"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"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/A5100613929","display_name":"Yafeng Zhang","orcid":"https://orcid.org/0000-0002-8890-7787","observed_orcids":["https://orcid.org/0000-0002-8890-7787"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yafeng Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100613929"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.47920000553131104,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.47920000553131104,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.30399999022483826,"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"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.050700001418590546,"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/functional-data-clustering","display_name":"functional data clustering","score":0.9710000157356262},{"id":"https://openalex.org/keywords/gene-expression-profiles","display_name":"gene expression profiles","score":0.7129999995231628},{"id":"https://openalex.org/keywords/dirichlet-process-mixture-model","display_name":"Dirichlet process mixture model","score":0.9599999785423279},{"id":"https://openalex.org/keywords/reproducing-kernel-hilbert-space","display_name":"reproducing kernel Hilbert space","score":0.7599999904632568},{"id":"https://openalex.org/keywords/phase-variation","display_name":"phase variation","score":0.7680000066757202}],"concepts":[{"id":"https://openalex.org/C51820054","wikidata":"https://www.wikidata.org/wiki/Q5508814","display_name":"Functional data analysis","level":2,"score":0.8954119682312012},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7636531591415405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.614356279373169},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5506913661956787},{"id":"https://openalex.org/C71176878","wikidata":"https://www.wikidata.org/wiki/Q17014987","display_name":"Functional principal component analysis","level":3,"score":0.5061270594596863},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4514613747596741},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.4497334063053131},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37590736150741577},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3355120122432709},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2589859664440155}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:escholarship.org/ark:/13030/qt0d01t79f","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/0d01t79f","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"etd"},{"id":"mag:86438764","doi":null,"is_oa":false,"landing_page_url":"https://escholarship.org/content/qt0d01t79f/qt0d01t79f.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W81822257","https://openalex.org/W328094392","https://openalex.org/W1500803570","https://openalex.org/W1528102277","https://openalex.org/W1587849410","https://openalex.org/W1596460436","https://openalex.org/W1698248478","https://openalex.org/W1913227953","https://openalex.org/W1964716164","https://openalex.org/W1967396577","https://openalex.org/W1967687583","https://openalex.org/W1968031931","https://openalex.org/W1974033269","https://openalex.org/W1974271203","https://openalex.org/W1987597996","https://openalex.org/W2011832962","https://openalex.org/W2017791169","https://openalex.org/W2018045523","https://openalex.org/W2018789523","https://openalex.org/W2019449965","https://openalex.org/W2019496134","https://openalex.org/W2033902994","https://openalex.org/W2039400412","https://openalex.org/W2039916829","https://openalex.org/W2044284788","https://openalex.org/W2049623660","https://openalex.org/W2059238813","https://openalex.org/W2060705109","https://openalex.org/W2062882942","https://openalex.org/W2064796257","https://openalex.org/W2068039256","https://openalex.org/W2069429561","https://openalex.org/W2072169887","https://openalex.org/W2079501320","https://openalex.org/W2080972498","https://openalex.org/W2089484716","https://openalex.org/W2091797506","https://openalex.org/W2092379933","https://openalex.org/W2097954556","https://openalex.org/W2098216772","https://openalex.org/W2101738966","https://openalex.org/W2102284541","https://openalex.org/W2102893853","https://openalex.org/W2103453943","https://openalex.org/W2106045204","https://openalex.org/W2112048220","https://openalex.org/W2119047368","https://openalex.org/W2127218421","https://openalex.org/W2128636568","https://openalex.org/W2135000328","https://openalex.org/W2142460132","https://openalex.org/W2146646206","https://openalex.org/W2148995578","https://openalex.org/W2150926065","https://openalex.org/W2151451331","https://openalex.org/W2151967501","https://openalex.org/W2156568029","https://openalex.org/W2161477969","https://openalex.org/W2162870748","https://openalex.org/W2166176031","https://openalex.org/W2167021978","https://openalex.org/W2343231218","https://openalex.org/W2405228168"],"related_works":["https://openalex.org/W2097934681","https://openalex.org/W2600168558","https://openalex.org/W1997095563","https://openalex.org/W2963664454","https://openalex.org/W2296355482","https://openalex.org/W7127656714","https://openalex.org/W1569686745","https://openalex.org/W145679802","https://openalex.org/W2885306251","https://openalex.org/W1968194079"],"abstract_inverted_index":{"Functional":[0,86,140],"data":[1,17,23,29,49,62,81,87,114,141,190,198,215],"analysis":[2,47,78],"aims":[3,89],"to":[4,90,108,128,168,247],"provide":[5],"statistical":[6],"inference":[7],"for":[8,197,213,271],"stochastic":[9],"processes":[10,53,137],"defined":[11,67],"over":[12,55,68],"a":[13,69,160,210],"functional":[14,22,61,80,113,189,214],"space.":[15],"Typical":[16],"sources,":[18],"often":[19],"modeled":[20],"using":[21],"analytic":[24],"techniques,":[25],"include:":[26],"nonlinear":[27],"longitudinal":[28],"in":[30,76,103,133,203,227,259],"biomedicine,":[31],"image":[32],"and":[33,84,98,138,185,217,235,250,262,266,273,278],"spatial":[34],"data,":[35,37,112,207],"space-time":[36],"etc.":[38],"This":[39],"dissertation":[40],"will":[41,59],"be":[42,165],"mainly":[43],"concerned":[44],"with":[45,95],"the":[46,77,134,170,228],"of":[48,79,93,118,130,153,155,225],"arising":[50],"from":[51],"bio-molecular":[52],"evolving":[54],"time.":[56],"Specifically,":[57],"we":[58,208],"consider":[60],"conceptualized":[63],"as":[64],"random":[65],"curves":[66,94,102,145,179,252],"time":[70,109,204],"domain.":[71],"Two":[72],"important":[73],"techniques":[74],"used":[75],"are":[82,126],"clustering":[83,88,115,193,216,274],"registration.":[85,218],"identify":[91],"subgroups":[92],"similar":[96,121],"shapes":[97],"estimate":[99],"representative":[100],"mean":[101],"each":[104],"cluster.":[105],"When":[106],"applied":[107],"course":[110,205],"genomics":[111,206],"identifies":[116],"clusters":[117,125],"genes":[119,131],"sharing":[120],"temporal":[122],"profiles.":[123],"These":[124],"likely":[127],"consist":[129],"involved":[132],"same":[135],"biological":[136],"functions.":[139],"registration":[142,191,272],"methods":[143],"align":[144],"exhibiting":[146],"phase":[147,186],"variability":[148],"(e.g.":[149],"variation":[150],"among":[151],"timings":[152],"features":[154],"different":[156],"curves).":[157],"After":[158],"alignment,":[159],"common":[161],"shape":[162,183],"function":[163],"can":[164],"estimated":[166],"consistently":[167],"represent":[169],"overall":[171],"pattern":[172],"shared":[173],"by":[174,201],"all":[175],"curves.":[176],"However,":[177],"when":[178],"show":[180,241,267],"both":[181,260],"systematic":[182],"differences":[184],"variability,":[187],"neither":[188],"nor":[192],"alone":[194],"is":[195,245],"appropriate":[196],"analysis.":[199],"Motivated":[200],"applications":[202],"propose":[209],"joint":[211],"model":[212,244],"The":[219],"proposed":[220],"method":[221],"integrates":[222],"reproducing":[223],"representations":[224],"functions":[226],"framework":[229],"on":[230,238],"Dirichlet":[231],"process":[232],"mixtures.":[233],"Simulation":[234],"case":[236,263],"studies":[237],"real":[239],"datasets":[240],"that":[242,268],"our":[243],"able":[246],"correctly":[248],"cluster":[249],"register":[251],"simultaneously.":[253],"We":[254],"explore":[255],"several":[256],"methodological":[257],"alternatives":[258],"synthetic":[261],"study":[264],"scenarios":[265],"jointly":[269],"accounting":[270],"produces":[275],"more":[276],"accurate":[277],"interpretable":[279],"inference.":[280]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}