{"id":"https://openalex.org/W4396514423","doi":"https://doi.org/10.1021/acs.jcim.4c00127","title":"Interpreting Neural Network Models for Toxicity Prediction by Extracting Learned Chemical Features","display_name":"Interpreting Neural Network Models for Toxicity Prediction by Extracting Learned Chemical Features","publication_year":2024,"publication_date":"2024-04-30","ids":{"openalex":"https://openalex.org/W4396514423","doi":"https://doi.org/10.1021/acs.jcim.4c00127","pmid":"https://pubmed.ncbi.nlm.nih.gov/38686880"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.4c00127","is_oa":true,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c00127","pdf_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00127","source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"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 Chemical Information and Modeling","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008780723","display_name":"Moritz Walter","orcid":"https://orcid.org/0009-0007-9021-3999"},"institutions":[{"id":"https://openalex.org/I71422933","display_name":"Sheffield Hallam University","ror":"https://ror.org/019wt1929","country_code":"GB","type":"education","lineage":["https://openalex.org/I71422933"]},{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Moritz Walter","raw_affiliation_strings":["Information School, University of Sheffield, The Wave, 2 Whitham Road, Sheffield S10 2AH, U.K"],"raw_orcid":"https://orcid.org/0009-0007-9021-3999","affiliations":[{"raw_affiliation_string":"Information School, University of Sheffield, The Wave, 2 Whitham Road, Sheffield S10 2AH, U.K","institution_ids":["https://openalex.org/I91136226","https://openalex.org/I71422933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011401103","display_name":"Samuel J. Webb","orcid":"https://orcid.org/0000-0003-1782-0921"},"institutions":[{"id":"https://openalex.org/I4210128146","display_name":"Canary Wharf Group (United Kingdom)","ror":"https://ror.org/02hx87760","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210128146"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Samuel J. Webb","raw_affiliation_strings":["Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PY, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1782-0921","affiliations":[{"raw_affiliation_string":"Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11 5PY, U.K","institution_ids":["https://openalex.org/I4210128146"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030046388","display_name":"Valerie J. Gillet","orcid":"https://orcid.org/0000-0002-8403-3111"},"institutions":[{"id":"https://openalex.org/I71422933","display_name":"Sheffield Hallam University","ror":"https://ror.org/019wt1929","country_code":"GB","type":"education","lineage":["https://openalex.org/I71422933"]},{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Valerie J. Gillet","raw_affiliation_strings":["Information School, University of Sheffield, The Wave, 2 Whitham Road, Sheffield S10 2AH, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8403-3111","affiliations":[{"raw_affiliation_string":"Information School, University of Sheffield, The Wave, 2 Whitham Road, Sheffield S10 2AH, U.K","institution_ids":["https://openalex.org/I91136226","https://openalex.org/I71422933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030046388"],"corresponding_institution_ids":["https://openalex.org/I71422933","https://openalex.org/I91136226"],"apc_list":null,"apc_paid":null,"fwci":4.3193,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.94896746,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"64","issue":"9","first_page":"3670","last_page":"3688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9991999864578247,"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":0.9991999864578247,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7701928019523621},{"id":"https://openalex.org/keywords/nexus","display_name":"Nexus (standard)","score":0.6958065032958984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6953725814819336},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6834997534751892},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6140676736831665},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4823964834213257}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7701928019523621},{"id":"https://openalex.org/C148609458","wikidata":"https://www.wikidata.org/wiki/Q7021281","display_name":"Nexus (standard)","level":2,"score":0.6958065032958984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6953725814819336},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6834997534751892},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6140676736831665},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4823964834213257},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1021/acs.jcim.4c00127","is_oa":true,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c00127","pdf_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00127","source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"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 Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:38686880","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38686880","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 chemical information and modeling","raw_type":null},{"id":"pmh:oai:eprints.whiterose.ac.uk:211994","is_oa":true,"landing_page_url":null,"pdf_url":"https://eprints.whiterose.ac.uk/211994/3/walter-et-al-2024-interpreting-neural-network-models-for-toxicity-prediction-by-extracting-learned-chemical-features.pdf","source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11094726","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11094726","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11094726/pdf/ci4c00127.pdf","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 Chem Inf Model","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1021/acs.jcim.4c00127","is_oa":true,"landing_page_url":"https://doi.org/10.1021/acs.jcim.4c00127","pdf_url":"https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00127","source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"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 Chemical Information and Modeling","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396514423.pdf","grobid_xml":"https://content.openalex.org/works/W4396514423.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W129251135","https://openalex.org/W1508604947","https://openalex.org/W1583837637","https://openalex.org/W1971014294","https://openalex.org/W1977340881","https://openalex.org/W1982597534","https://openalex.org/W1988195734","https://openalex.org/W1995370815","https://openalex.org/W1999798000","https://openalex.org/W2002503643","https://openalex.org/W2033757486","https://openalex.org/W2038557382","https://openalex.org/W2066532920","https://openalex.org/W2080086479","https://openalex.org/W2103252267","https://openalex.org/W2114043871","https://openalex.org/W2136588642","https://openalex.org/W2168480393","https://openalex.org/W2189911347","https://openalex.org/W2294213638","https://openalex.org/W2396490691","https://openalex.org/W2420245003","https://openalex.org/W2473190403","https://openalex.org/W2513653040","https://openalex.org/W2556851635","https://openalex.org/W2594183968","https://openalex.org/W2760085125","https://openalex.org/W2792641098","https://openalex.org/W2904528875","https://openalex.org/W2907473220","https://openalex.org/W2909055772","https://openalex.org/W2919115771","https://openalex.org/W2921802966","https://openalex.org/W2946617578","https://openalex.org/W2977595407","https://openalex.org/W2978238437","https://openalex.org/W2981836045","https://openalex.org/W3022298391","https://openalex.org/W3030978062","https://openalex.org/W3085380432","https://openalex.org/W3093687066","https://openalex.org/W3100711616","https://openalex.org/W3124172763","https://openalex.org/W3131648425","https://openalex.org/W3133900975","https://openalex.org/W3136947284","https://openalex.org/W4210436046","https://openalex.org/W4212774754","https://openalex.org/W4220763949","https://openalex.org/W4224232334","https://openalex.org/W4229494842","https://openalex.org/W4234423219","https://openalex.org/W4283066927","https://openalex.org/W4297814571","https://openalex.org/W4298061300","https://openalex.org/W4362503491","https://openalex.org/W4382280502","https://openalex.org/W4386170274","https://openalex.org/W4386587901","https://openalex.org/W4389307242"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Neural":[0],"network":[1],"models":[2,30],"have":[3,61],"become":[4],"a":[5,91],"popular":[6],"machine-learning":[7],"technique":[8,93],"for":[9,109,140],"the":[10,52,110,119,127,134,143,153,156],"toxicity":[11],"prediction":[12],"of":[13,55,76,112,121,155],"chemicals.":[14],"However,":[15],"due":[16],"to":[17,24,36,51,94,106,132,168],"their":[18],"complex":[19],"structure,":[20],"it":[21],"is":[22,124],"difficult":[23],"understand":[25],"predictions":[26],"made":[27],"by":[28,48],"these":[29,59],"which":[31,83,98],"limits":[32],"confidence.":[33],"Current":[34],"techniques":[35],"tackle":[37],"this":[38],"problem":[39],"such":[40],"as":[41,148],"SHAP":[42],"or":[43],"integrated":[44],"gradients":[45],"provide":[46],"insights":[47],"attributing":[49],"importance":[50,120],"input":[53],"features":[54],"individual":[56,116],"compounds.":[57],"While":[58],"methods":[60],"produced":[62],"promising":[63],"results":[64],"in":[65,80,102],"some":[66],"cases,":[67],"they":[68],"do":[69],"not":[70],"shed":[71],"light":[72],"on":[73],"how":[74,85],"representations":[75],"compounds":[77],"are":[78,130,163],"transformed":[79],"hidden":[81,113,122],"layers,":[82],"constitute":[84],"neural":[86,96],"networks":[87,97],"learn.":[88],"We":[89],"present":[90],"novel":[92],"interpret":[95],"identifies":[99],"chemical":[100],"substructures":[101,129],"training":[103],"data":[104],"found":[105],"be":[107],"responsible":[108],"activation":[111],"neurons.":[114],"For":[115],"test":[117],"compounds,":[118],"neurons":[123],"determined,":[125],"and":[126,158,166],"associated":[128],"leveraged":[131],"explain":[133],"model":[135,161],"prediction.":[136],"Using":[137],"structural":[138],"alerts":[139],"mutagenicity":[141],"from":[142,171],"Derek":[144],"Nexus":[145],"expert":[146],"system":[147],"ground":[149],"truth,":[150],"we":[151],"demonstrate":[152],"validity":[154],"approach":[157],"show":[159],"that":[160],"explanations":[162,169],"competitive":[164],"with":[165],"complementary":[167],"obtained":[170],"an":[172],"established":[173],"feature":[174],"attribution":[175],"method.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-22T09:01:20.584952","created_date":"2025-10-10T00:00:00"}