{"id":"https://openalex.org/W2731161895","doi":"https://doi.org/10.1186/s13321-017-0226-y","title":"Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data","display_name":"Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data","publication_year":2017,"publication_date":"2017-06-28","ids":{"openalex":"https://openalex.org/W2731161895","doi":"https://doi.org/10.1186/s13321-017-0226-y","mag":"2731161895","pmid":"https://pubmed.ncbi.nlm.nih.gov/29086090"},"language":"en","primary_location":{"id":"doi:10.1186/s13321-017-0226-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-017-0226-y","pdf_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-017-0226-y","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-017-0226-y","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076832707","display_name":"Alexios Koutsoukas","orcid":null},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alexios Koutsoukas","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015122838","display_name":"Keith J. Monaghan","orcid":null},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keith J. Monaghan","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418684","display_name":"Xiaoli Li","orcid":"https://orcid.org/0000-0002-0762-6562"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoli Li","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105352906","display_name":"Jun Huan","orcid":"https://orcid.org/0000-0003-4929-2617"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Huan","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA. jhuan@ittc.ku.edu","Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA"],"raw_orcid":"https://orcid.org/0000-0003-4929-2617","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA. jhuan@ittc.ku.edu","institution_ids":["https://openalex.org/I146416000"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of Kansas, Lawrence, KS, 66047-7621, USA","institution_ids":["https://openalex.org/I146416000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076832707"],"corresponding_institution_ids":["https://openalex.org/I146416000"],"apc_list":{"value":1290,"currency":"GBP","value_usd":1582},"apc_paid":{"value":1290,"currency":"GBP","value_usd":1582},"fwci":21.2822,"has_fulltext":true,"cited_by_count":318,"citation_normalized_percentile":{"value":0.99640119,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"9","issue":"1","first_page":"42","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9093999862670898,"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"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9093999862670898,"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"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.035599999129772186,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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":0.007899999618530273,"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/deep-learning","display_name":"Deep learning","score":0.7322929501533508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7175276279449463},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6628260612487793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6604739427566528},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.608709454536438},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.593075156211853},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39479097723960876},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3827309012413025}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7322929501533508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7175276279449463},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6628260612487793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6604739427566528},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.608709454536438},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.593075156211853},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39479097723960876},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3827309012413025}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1186/s13321-017-0226-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-017-0226-y","pdf_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-017-0226-y","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},{"id":"pmid:29086090","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29086090","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 cheminformatics","raw_type":null},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/179481","is_oa":true,"landing_page_url":"https://scholarbank.nus.edu.sg/handle/10635/179481","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Unpaywall 20201031","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:b3ecb9e27e234057ac0f5202175666f9","is_oa":false,"landing_page_url":"https://doaj.org/article/b3ecb9e27e234057ac0f5202175666f9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Cheminformatics, Vol 9, Iss 1, Pp 1-13 (2017)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:5489441","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5489441","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Cheminform","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s13321-017-0226-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-017-0226-y","pdf_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-017-0226-y","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3556525442","display_name":null,"funder_award_id":"CNS 1337899","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5801408398","display_name":null,"funder_award_id":"Tesla K40","funder_id":"https://openalex.org/F4320309480","funder_display_name":"Nvidia"},{"id":"https://openalex.org/G8721421696","display_name":null,"funder_award_id":"1337899","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2731161895.pdf","grobid_xml":"https://content.openalex.org/works/W2731161895.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W12970924","https://openalex.org/W17285715","https://openalex.org/W1498436455","https://openalex.org/W1520812622","https://openalex.org/W1550206324","https://openalex.org/W1552041072","https://openalex.org/W1924689489","https://openalex.org/W1971256926","https://openalex.org/W1975875968","https://openalex.org/W1978508948","https://openalex.org/W1983515051","https://openalex.org/W1983691152","https://openalex.org/W1985258161","https://openalex.org/W1988037271","https://openalex.org/W1988195734","https://openalex.org/W1988856281","https://openalex.org/W1988909822","https://openalex.org/W1991537916","https://openalex.org/W1995341919","https://openalex.org/W1998399571","https://openalex.org/W1999798000","https://openalex.org/W2007697155","https://openalex.org/W2011422283","https://openalex.org/W2025666819","https://openalex.org/W2028070629","https://openalex.org/W2034027234","https://openalex.org/W2035424729","https://openalex.org/W2037788267","https://openalex.org/W2039196793","https://openalex.org/W2040369353","https://openalex.org/W2041610798","https://openalex.org/W2046589863","https://openalex.org/W2046653925","https://openalex.org/W2060062036","https://openalex.org/W2079223054","https://openalex.org/W2090240212","https://openalex.org/W2095705004","https://openalex.org/W2096541451","https://openalex.org/W2099094031","https://openalex.org/W2101234009","https://openalex.org/W2103359087","https://openalex.org/W2107432340","https://openalex.org/W2109553965","https://openalex.org/W2118585731","https://openalex.org/W2119387367","https://openalex.org/W2119821739","https://openalex.org/W2132424367","https://openalex.org/W2140833774","https://openalex.org/W2141125852","https://openalex.org/W2149150765","https://openalex.org/W2152932486","https://openalex.org/W2153635508","https://openalex.org/W2155893237","https://openalex.org/W2163614729","https://openalex.org/W2163922914","https://openalex.org/W2171830166","https://openalex.org/W2189911347","https://openalex.org/W2213443318","https://openalex.org/W2234529989","https://openalex.org/W2295862081","https://openalex.org/W2315837940","https://openalex.org/W2329862012","https://openalex.org/W2332135472","https://openalex.org/W2384495648","https://openalex.org/W2397757171","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W4250981202","https://openalex.org/W4252684946"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4380075502","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"BACKGROUND:":[0],"In":[1],"recent":[2],"years,":[3],"research":[4],"in":[5,26,40,89],"artificial":[6],"neural":[7,152],"networks":[8,153],"has":[9,33],"resurged,":[10],"now":[11],"under":[12],"the":[13,65,90,180,195,284,297],"deep-learning":[14,123],"umbrella,":[15],"and":[16,29,42,69,78,101,125,161,188,237,293],"grown":[17],"extremely":[18],"popular.":[19],"Recently":[20],"reported":[21],"success":[22],"of":[23,47,55,67,92,107,114,140,156,190,220,265,279,300],"DL":[24],"techniques":[25],"crowd-sourced":[27],"QSAR":[28],"predictive":[30],"toxicology":[31,43],"competitions":[32],"showcased":[34],"these":[35],"methods":[36,86,110,164,254,305],"as":[37,72],"powerful":[38],"tools":[39],"drug-discovery":[41],"research.":[44],"The":[45,120],"aim":[46],"this":[48,135],"work":[49],"was":[50,82,118,288],"dual,":[51],"first":[52],"large":[53,138],"number":[54,139,185,189],"hyper-parameter":[56],"configurations":[57,142],"were":[58,130,173,200,255],"explored":[59],"to":[60,84,111,132,143,175,194,202,251,257,271,290],"investigate":[61],"how":[62],"they":[63],"affect":[64],"performance":[66,81,160],"DNNs":[68,77,199],"could":[70],"act":[71],"starting":[73],"points":[74],"when":[75,169,260,274],"tuning":[76],"second":[79],"their":[80],"compared":[83,193],"popular":[85],"widely":[87],"employed":[88],"field":[91],"cheminformatics":[93],"namely":[94],"Na\u00efve":[95,285],"Bayes,":[96],"k-nearest":[97],"neighbor,":[98],"random":[99],"forest":[100],"support":[102],"vector":[103],"machines.":[104],"Moreover,":[105],"robustness":[106,250],"machine":[108],"learning":[109],"different":[112],"levels":[113,264,278],"artificially":[115],"introduced":[116],"noise":[117,301],"assessed.":[119],"open-source":[121],"Caffe":[122],"framework":[124],"modern":[126],"NVidia":[127],"GPU":[128],"units":[129,219],"utilized":[131],"carry":[133],"out":[134],"study,":[136],"allowing":[137],"DNN":[141,214],"be":[144],"explored.":[145],"RESULTS:":[146],"We":[147],"show":[148],"that":[149,172],"feed-forward":[150],"deep":[151],"are":[154,179],"capable":[155],"achieving":[157],"strong":[158],"classification":[159],"outperform":[162,295],"shallow":[163],"across":[165,306],"diverse":[166],"activity":[167],"classes":[168],"optimized.":[170],"Hyper-parameters":[171],"found":[174,201,256,289],"play":[176],"critical":[177],"role":[178],"activation":[181],"function,":[182],"dropout":[183],"regularization,":[184],"hidden":[186],"layers":[187],"neurons.":[191],"When":[192,248],"rest":[196],"methods,":[197],"tuned":[198],"statistically":[203],"outperform,":[204],"with":[205,231,243,262,276],"p":[206],"value":[207],"<0.01":[208],"based":[209],"on":[210,216],"Wilcoxon":[211],"statistical":[212],"test.":[213],"achieved":[215],"average":[217],"MCC":[218],"0.149":[221],"higher":[222,240,277,281],"than":[223,226,229,235,241,268,282],"NB,":[224],"0.092":[225],"kNN,":[227],"0.052":[228],"SVM":[230,242],"linear":[232],"kernel,":[233],"0.021":[234],"RF":[236],"finally":[238],"0.009":[239],"radial":[244],"basis":[245],"function":[246],"kernel.":[247],"exploring":[249],"noise,":[252,266,280],"non-linear":[253],"perform":[258,291],"well":[259,292],"dealing":[261,275],"low":[263],"lower":[267],"or":[269],"equal":[270],"20%,":[272],"however":[273],"30%,":[283],"Bayes":[286],"method":[287],"even":[294],"at":[296],"highest":[298],"level":[299],"50%":[302],"more":[303],"sophisticated":[304],"several":[307],"datasets.":[308]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":42},{"year":2023,"cited_by_count":45},{"year":2022,"cited_by_count":54},{"year":2021,"cited_by_count":57},{"year":2020,"cited_by_count":34},{"year":2019,"cited_by_count":32},{"year":2018,"cited_by_count":22},{"year":2017,"cited_by_count":1}],"updated_date":"2026-05-09T13:55:54.758798","created_date":"2025-10-10T00:00:00"}