{"id":"https://openalex.org/W2485373132","doi":"https://doi.org/10.1142/s021972001650030x","title":"Alignment of time-resolved data from high throughput experiments","display_name":"Alignment of time-resolved data from high throughput experiments","publication_year":2016,"publication_date":"2016-08-03","ids":{"openalex":"https://openalex.org/W2485373132","doi":"https://doi.org/10.1142/s021972001650030x","mag":"2485373132","pmid":"https://pubmed.ncbi.nlm.nih.gov/27629153"},"language":"en","primary_location":{"id":"doi:10.1142/s021972001650030x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021972001650030x","pdf_url":null,"source":{"id":"https://openalex.org/S155349577","display_name":"Journal of Bioinformatics and Computational Biology","issn_l":"0219-7200","issn":["0219-7200","1757-6334"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Bioinformatics and Computational Biology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5009756123","display_name":"Nada Abidi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124929","display_name":"Helmholtz Centre for Infection Research","ror":"https://ror.org/03d0p2685","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I4210124929"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Nada Abidi","raw_affiliation_strings":["Biostatistics, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124 Braunschweig, Germany"],"affiliations":[{"raw_affiliation_string":"Biostatistics, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124 Braunschweig, Germany","institution_ids":["https://openalex.org/I4210124929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057865858","display_name":"Raimo Franke","orcid":"https://orcid.org/0000-0002-5407-5521"},"institutions":[{"id":"https://openalex.org/I4210124929","display_name":"Helmholtz Centre for Infection Research","ror":"https://ror.org/03d0p2685","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I4210124929"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Raimo Franke","raw_affiliation_strings":["Chemical Biology, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124 Braunschweig, Germany"],"affiliations":[{"raw_affiliation_string":"Chemical Biology, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124 Braunschweig, Germany","institution_ids":["https://openalex.org/I4210124929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047706269","display_name":"Peter Findeisen","orcid":null},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]},{"id":"https://openalex.org/I4210156450","display_name":"University Medical Centre Mannheim","ror":"https://ror.org/05sxbyd35","country_code":"DE","type":"funder","lineage":["https://openalex.org/I4210156450"]},{"id":"https://openalex.org/I2802164966","display_name":"University Hospital Heidelberg","ror":"https://ror.org/013czdx64","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2802164966"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Peter Findeisen","raw_affiliation_strings":["Institute for Clinical Chemistry, Medical Faculty Mannheim, Heidelberg University Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim, Germany"],"affiliations":[{"raw_affiliation_string":"Institute for Clinical Chemistry, Medical Faculty Mannheim, Heidelberg University Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim, Germany","institution_ids":["https://openalex.org/I4210156450","https://openalex.org/I223822909","https://openalex.org/I2802164966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049605606","display_name":"Frank Klawonn","orcid":"https://orcid.org/0000-0001-9613-182X"},"institutions":[{"id":"https://openalex.org/I4210124929","display_name":"Helmholtz Centre for Infection Research","ror":"https://ror.org/03d0p2685","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I4210124929"]},{"id":"https://openalex.org/I2799859273","display_name":"Ostfalia University of Applied Sciences","ror":"https://ror.org/01bk10867","country_code":"DE","type":"education","lineage":["https://openalex.org/I2799859273"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frank Klawonn","raw_affiliation_strings":["Biostatistics, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124 Braunschweig, Germany","Department of Computer Science, Ostfalia University of Applied Sciences Salzdahlumer Str. 46/48, D-38302 Wolfenbuettel, Germany"],"affiliations":[{"raw_affiliation_string":"Biostatistics, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124 Braunschweig, Germany","institution_ids":["https://openalex.org/I4210124929"]},{"raw_affiliation_string":"Department of Computer Science, Ostfalia University of Applied Sciences Salzdahlumer Str. 46/48, D-38302 Wolfenbuettel, Germany","institution_ids":["https://openalex.org/I2799859273"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009756123"],"corresponding_institution_ids":["https://openalex.org/I4210124929"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06209573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"06","first_page":"1650030","last_page":"1650030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.995199978351593,"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/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8849879503250122},{"id":"https://openalex.org/keywords/equidistant","display_name":"Equidistant","score":0.7793800830841064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5578852891921997},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5559768080711365},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5157740116119385},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4730469584465027},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.43462252616882324},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38794100284576416},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33015668392181396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22652167081832886},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13653317093849182},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.13619303703308105},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10909610986709595}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8849879503250122},{"id":"https://openalex.org/C158245278","wikidata":"https://www.wikidata.org/wiki/Q4386982","display_name":"Equidistant","level":2,"score":0.7793800830841064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5578852891921997},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5559768080711365},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5157740116119385},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4730469584465027},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.43462252616882324},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38794100284576416},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33015668392181396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22652167081832886},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13653317093849182},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.13619303703308105},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10909610986709595},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002851","descriptor_name":"Chromatography, High Pressure Liquid","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057166","descriptor_name":"High-Throughput Screening Assays","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010455","descriptor_name":"Peptides","qualifier_ui":"Q000097","qualifier_name":"blood","is_major_topic":false},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D053719","descriptor_name":"Tandem Mass Spectrometry","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002851","descriptor_name":"Chromatography, High Pressure Liquid","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057166","descriptor_name":"High-Throughput Screening Assays","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010455","descriptor_name":"Peptides","qualifier_ui":"Q000097","qualifier_name":"blood","is_major_topic":false},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D053719","descriptor_name":"Tandem Mass Spectrometry","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002851","descriptor_name":"Chromatography, High Pressure Liquid","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057166","descriptor_name":"High-Throughput Screening Assays","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010455","descriptor_name":"Peptides","qualifier_ui":"Q000097","qualifier_name":"blood","is_major_topic":false},{"descriptor_ui":"D016415","descriptor_name":"Sequence Alignment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D053719","descriptor_name":"Tandem Mass Spectrometry","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1142/s021972001650030x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021972001650030x","pdf_url":null,"source":{"id":"https://openalex.org/S155349577","display_name":"Journal of Bioinformatics and Computational Biology","issn_l":"0219-7200","issn":["0219-7200","1757-6334"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Bioinformatics and Computational Biology","raw_type":"journal-article"},{"id":"pmid:27629153","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27629153","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of bioinformatics and computational biology","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W148362043","https://openalex.org/W207223910","https://openalex.org/W1501400124","https://openalex.org/W1689907099","https://openalex.org/W1944641399","https://openalex.org/W1999517677","https://openalex.org/W2011907162","https://openalex.org/W2026143282","https://openalex.org/W2036384011","https://openalex.org/W2056589723","https://openalex.org/W2093767384","https://openalex.org/W2132585078","https://openalex.org/W2140541142","https://openalex.org/W2159760706","https://openalex.org/W2169387693","https://openalex.org/W2323712034"],"related_works":["https://openalex.org/W2055230676","https://openalex.org/W2609942398","https://openalex.org/W2764033112","https://openalex.org/W3092399163","https://openalex.org/W4380451100","https://openalex.org/W2772616816","https://openalex.org/W4205256820","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"To":[0],"better":[1],"understand":[2],"the":[3,6,32,56,66,80,83,86,89,125,144,151,159,177,195,212,287],"dynamics":[4],"of":[5,34,58,82,194,235,294,305,317],"underlying":[7],"processes":[8],"in":[9,49,131,231,286],"cells,":[10],"it":[11,217],"is":[12,61,121,169,183,190,237,337,348,359],"necessary":[13],"to":[14,30,52,108,123,128,133,172,266,274,296,323],"take":[15],"measurements":[16,67,222,249,329],"over":[17],"a":[18,94,102,109,136,170,291,314],"time":[19,54,59,72,153,187,200,205,226,246,254,281,326,332],"course.":[20],"Modern":[21],"high-throughput":[22,271],"technologies":[23],"are":[24,68,79,161,164],"often":[25],"used":[26,265],"for":[27,77,154,199,256],"this":[28,78,208],"purpose":[29],"measure":[31],"behavior":[33,91],"cell":[35],"products":[36],"like":[37],"metabolites,":[38],"peptides,":[39],"proteins,":[40],"[Formula:":[41],"see":[42],"text]RNA":[43],"or":[44,175],"mRNA":[45],"at":[46,70,150,223,330],"different":[47,257],"points":[48,60,227,255,327],"time.":[50],"Compared":[51],"classical":[53],"series,":[55],"number":[57],"usually":[62,92,238],"very":[63],"limited":[64],"and":[65,85,97,104,127,157,273,283],"taken":[69],"irregular":[71,245],"intervals.":[73],"The":[74,140,334,346],"main":[75],"reasons":[76],"costs":[81],"experiments":[84,126,272],"fact":[87],"that":[88,143,158,216,320],"dynamic":[90],"shows":[93],"strong":[95],"reaction":[96],"fast":[98],"changes":[99],"shortly":[100],"after":[101],"stimulus":[103,146],"then":[105],"slowly":[106],"converges":[107],"certain":[110],"stable":[111],"state.":[112],"Another":[113],"reason":[114],"might":[115],"simply":[116],"be":[117,263],"missing":[118],"values.":[119],"It":[120],"common":[122,196],"repeat":[124],"have":[129,324],"replicates":[130,156,160],"order":[132],"carry":[134],"out":[135],"more":[137],"reliable":[138],"analysis.":[139],"ideal":[141],"assumptions":[142],"initial":[145],"really":[147],"started":[148],"exactly":[149],"same":[152],"all":[155],"perfectly":[162],"synchronized":[163],"seldom":[165],"satisfied.":[166],"Therefore,":[167],"there":[168],"need":[171,322],"first":[173],"adjust":[174],"align":[176,219,267],"time-resolved":[178,241,268,301],"data":[179,202,236,242,269,302,356],"before":[180],"further":[181],"analysis":[182],"carried":[184],"out.":[185],"Dynamic":[186],"warping":[188],"(DTW)":[189],"considered":[191],"as":[192,240,250,252,280,341,343,350],"one":[193],"alignment":[197,316],"techniques":[198],"series":[201],"with":[203,221,228,339],"equidistant":[204],"points.":[206,333],"In":[207],"paper,":[209],"we":[210],"modified":[211,292],"DTW":[213,295],"algorithm":[214,261],"so":[215],"can":[218,262],"sequences":[220,319],"different,":[224],"non-equidistant":[225],"large":[229],"gaps":[230],"between.":[232],"This":[233,259],"type":[234],"known":[239],"characterized":[243],"by":[244,300,303],"intervals":[247],"between":[248],"well":[251,342],"non-identical":[253],"replicates.":[258],"new":[260],"easily":[264],"from":[270],"come":[275],"across":[276],"existing":[277,284],"problems":[278],"such":[279],"scarcity":[282],"noise":[285],"measurements.":[288],"We":[289],"propose":[290],"method":[293,336],"adapt":[297],"requirements":[298],"imposed":[299],"use":[304],"monotone":[306],"cubic":[307],"interpolation":[308],"splines.":[309],"Our":[310],"presented":[311],"approach":[312],"provides":[313],"nonlinear":[315],"two":[318],"neither":[321],"equi-distant":[325],"nor":[328],"identical":[331],"proposed":[335],"evaluated":[338],"artificial":[340],"real":[344],"data.":[345],"software":[347],"available":[349,361],"an":[351],"R":[352],"package":[353],"tra":[354],"(Time-Resolved":[355],"Alignment)":[357],"which":[358],"freely":[360],"at:":[362],"http://public.ostfalia.de/klawonn/tra.zip":[363],".":[364]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}