{"id":"https://openalex.org/W2773807301","doi":"https://doi.org/10.1109/bibm.2017.8217677","title":"The relative importance of data points in systems biology and parameter estimation","display_name":"The relative importance of data points in systems biology and parameter estimation","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2773807301","doi":"https://doi.org/10.1109/bibm.2017.8217677","mag":"2773807301"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2017.8217677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2017.8217677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5051281569","display_name":"Jenny Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jenny Jeong","raw_affiliation_strings":["Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041343853","display_name":"Peng Qiu","orcid":"https://orcid.org/0000-0003-3256-0734"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Qiu","raw_affiliation_strings":["Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444","https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051281569"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14535179,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"367","last_page":"373"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9995999932289124,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9995999932289124,"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/T11764","display_name":"Evolution and Genetic Dynamics","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/T10932","display_name":"Microbial Metabolic Engineering and Bioproduction","score":0.9891999959945679,"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/mean-squared-error","display_name":"Mean squared error","score":0.6005109548568726},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5736091136932373},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.5717154741287231},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5529223680496216},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5318018794059753},{"id":"https://openalex.org/keywords/square","display_name":"Square (algebra)","score":0.4973345100879669},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.47001150250434875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4641396403312683},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4630665183067322},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.46165478229522705},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.4543343186378479},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44335564970970154},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4202670454978943},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38413843512535095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.26372694969177246}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6005109548568726},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5736091136932373},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.5717154741287231},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5529223680496216},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5318018794059753},{"id":"https://openalex.org/C135692309","wikidata":"https://www.wikidata.org/wiki/Q111124","display_name":"Square (algebra)","level":2,"score":0.4973345100879669},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.47001150250434875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4641396403312683},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4630665183067322},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.46165478229522705},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.4543343186378479},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44335564970970154},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4202670454978943},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38413843512535095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26372694969177246},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2017.8217677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2017.8217677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1985911638","https://openalex.org/W2014382043","https://openalex.org/W2016966551","https://openalex.org/W2019143734","https://openalex.org/W2069647329","https://openalex.org/W2071563913","https://openalex.org/W2080573473","https://openalex.org/W2086215140","https://openalex.org/W2100560953","https://openalex.org/W2103776834","https://openalex.org/W2109571753","https://openalex.org/W2118891267","https://openalex.org/W2119986464","https://openalex.org/W2122930146","https://openalex.org/W2142676005","https://openalex.org/W2146230717","https://openalex.org/W2154601808","https://openalex.org/W2295803031"],"related_works":["https://openalex.org/W2102148524","https://openalex.org/W3102623159","https://openalex.org/W2314720829","https://openalex.org/W4385074335","https://openalex.org/W2366911843","https://openalex.org/W2626189183","https://openalex.org/W2350577681","https://openalex.org/W2014418584","https://openalex.org/W2949338837","https://openalex.org/W2076173359"],"abstract_inverted_index":{"Estimating":[0],"model":[1,37,51,113,196],"parameters":[2,38],"is":[3,22,68,83,99,106,160],"a":[4,18,55,193,205],"crucial":[5],"step":[6],"to":[7,111,139,143,208,215],"understand":[8],"the":[9,23,29,36,41,44,62,65,81,101,112,122,130,134,149,167,171,216,221,224],"behavior":[10],"of":[11,43,64,90,103,125,133,156,211,223],"biological":[12],"systems.":[13],"To":[14,187],"perform":[15],"parameter":[16,59,116,212],"estimation,":[17],"commonly":[19],"used":[20,192],"formulation":[21,56,73],"least":[24,71,150],"square":[25,72,151],"method":[26,34],"that":[27,39,84,100,179],"minimizes":[28],"mean":[30],"squared":[31,45],"error.":[32],"This":[33,67],"finds":[35],"minimize":[40],"sum":[42],"error":[46],"between":[47],"experimental":[48,104],"data":[49,77,87,105,126,145,158,168,175,185],"and":[50,61,119,201,219],"predictions.":[52],"However,":[53],"such":[54],"can":[57],"misguide":[58],"estimation":[60,117],"understanding":[63],"system.":[66],"mainly":[69],"because":[70],"typically":[74],"treats":[75],"all":[76,86],"points":[78,88,127],"equally,":[79],"while":[80],"reality":[82],"not":[85],"are":[89],"equal":[91],"importance.":[92],"Another":[93],"common":[94],"issue":[95],"in":[96],"systems":[97],"biology":[98],"amount":[102],"almost":[107],"always":[108],"limited":[109],"compared":[110],"complexity,":[114],"making":[115],"challenging":[118],"ill-conditioned.":[120],"Ignoring":[121],"relative":[123],"importance":[124],"may":[128],"amplify":[129],"ill-conditioned":[131],"nature":[132],"problem.":[135],"Therefore,":[136],"we":[137,191],"propose":[138],"give":[140],"different":[141],"weight":[142,155],"each":[144,157,174],"point":[146,159,169],"when":[147],"formulating":[148],"cost":[152,227],"function.":[153],"The":[154],"defined":[161],"by":[162],"an":[163],"uncertainty":[164],"measure":[165],"for":[166],"given":[170],"others,":[172],"quantifying":[173],"point's":[176],"unique":[177],"information":[178],"cannot":[180],"be":[181],"inferred":[182],"from":[183],"other":[184],"points.":[186],"test":[188],"our":[189],"algorithm,":[190],"G1/S":[194],"transition":[195],"with":[197],"two":[198],"dynamic":[199],"variables":[200],"12":[202],"parameters,":[203],"developed":[204],"sampling":[206],"algorithm":[207],"obtain":[209],"collections":[210],"settings":[213],"close":[214],"best":[217],"fit,":[218],"demonstrated":[220],"benefits":[222],"proposed":[225],"weighted":[226],"function":[228],"formulation.":[229]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}