{"id":"https://openalex.org/W4401066992","doi":"https://doi.org/10.1093/bioinformatics/btae359","title":"A deep learning architecture for metabolic pathway prediction","display_name":"A deep learning architecture for metabolic pathway prediction","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4401066992","doi":"https://doi.org/10.1093/bioinformatics/btae359"},"language":"en","primary_location":{"id":"doi:10.1093/bioinformatics/btae359","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btae359","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/40/7/btae359/58667783/btae359.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://academic.oup.com/bioinformatics/article-pdf/40/7/btae359/58667783/btae359.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085311610","display_name":"Mayank Baranwal","orcid":"https://orcid.org/0000-0001-9354-2826"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mayank Baranwal","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan , Ann Arbor, MI 48109, USA"],"raw_orcid":"https://orcid.org/0000-0001-9354-2826","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan , Ann Arbor, MI 48109, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004115333","display_name":"Abram Magner","orcid":"https://orcid.org/0000-0002-3082-9915"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abram Magner","raw_affiliation_strings":["Department of Computer Science, University at Albany , SUNY, Albany, NY 12222, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Albany , SUNY, Albany, NY 12222, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038460282","display_name":"Paolo Elvati","orcid":"https://orcid.org/0000-0002-6882-6023"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paolo Elvati","raw_affiliation_strings":["Department of Mechanical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035589705","display_name":"Jacob C. Saldinger","orcid":"https://orcid.org/0000-0001-5005-614X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jacob Saldinger","raw_affiliation_strings":["Department of Mechanical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051408642","display_name":"Angela Violi","orcid":"https://orcid.org/0000-0001-9517-668X"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Angela Violi","raw_affiliation_strings":["Department of Chemical Engineering and Biophysics, University of Michigan , Ann Arbor, MI 48109, USA","Department of Mechanical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering and Biophysics, University of Michigan , Ann Arbor, MI 48109, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Department of Mechanical Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077692655","display_name":"Alfred O. Hero","orcid":"https://orcid.org/0000-0002-2531-9670"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfred O Hero","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan , Ann Arbor, MI 48109, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan , Ann Arbor, MI 48109, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3618,"currency":"USD","value_usd":3618},"apc_paid":{"value":3618,"currency":"USD","value_usd":3618},"fwci":2.8842,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9178519,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"40","issue":"7","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T10932","display_name":"Microbial Metabolic Engineering and Bioproduction","score":0.9957000017166138,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9951000213623047,"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/computer-science","display_name":"Computer science","score":0.7428595423698425},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6034923791885376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5975285172462463},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5821315050125122},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5579494833946228},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49874162673950195},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4767088294029236},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.4393211901187897},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4317816495895386},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42193442583084106},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41538581252098083},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24644440412521362},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.13981986045837402},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.0853222906589508}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7428595423698425},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6034923791885376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5975285172462463},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5821315050125122},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5579494833946228},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49874162673950195},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4767088294029236},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.4393211901187897},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4317816495895386},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42193442583084106},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41538581252098083},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24644440412521362},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.13981986045837402},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0853222906589508},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1093/bioinformatics/btae359","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btae359","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/40/7/btae359/58667783/btae359.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11775948","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11775948","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11775948/pdf/btae359.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":"Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1093/bioinformatics/btae359","is_oa":true,"landing_page_url":"https://doi.org/10.1093/bioinformatics/btae359","pdf_url":"https://academic.oup.com/bioinformatics/article-pdf/40/7/btae359/58667783/btae359.pdf","source":{"id":"https://openalex.org/S52395412","display_name":"Bioinformatics","issn_l":"1367-4803","issn":["1367-4803","1367-4811"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G2279853913","display_name":null,"funder_award_id":"W911NF-19-1","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G3424441068","display_name":null,"funder_award_id":"W911NF-14-1","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G6520853767","display_name":null,"funder_award_id":"W911NF-14-1-0359","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8415477955","display_name":null,"funder_award_id":"W911NF-19","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8887290759","display_name":null,"funder_award_id":"W911NF-19-1-0269","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4401066992.pdf"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1574994167","https://openalex.org/W1761787460","https://openalex.org/W1797956629","https://openalex.org/W1972763168","https://openalex.org/W1981885395","https://openalex.org/W1996662136","https://openalex.org/W1997996256","https://openalex.org/W1999798000","https://openalex.org/W2004467618","https://openalex.org/W2029574260","https://openalex.org/W2040895929","https://openalex.org/W2047583216","https://openalex.org/W2052907531","https://openalex.org/W2058501095","https://openalex.org/W2066273100","https://openalex.org/W2070587756","https://openalex.org/W2098561597","https://openalex.org/W2101234009","https://openalex.org/W2104869668","https://openalex.org/W2105649494","https://openalex.org/W2112411768","https://openalex.org/W2112692578","https://openalex.org/W2113531097","https://openalex.org/W2129860849","https://openalex.org/W2137450588","https://openalex.org/W2153344191","https://openalex.org/W2165674132","https://openalex.org/W2167277498","https://openalex.org/W2168465568","https://openalex.org/W2169303530","https://openalex.org/W2189911347","https://openalex.org/W2190425105","https://openalex.org/W2301231318","https://openalex.org/W2344676116","https://openalex.org/W2473839515","https://openalex.org/W2507720777","https://openalex.org/W2574386421","https://openalex.org/W2742248058","https://openalex.org/W2752875642","https://openalex.org/W2761434131","https://openalex.org/W2766352633","https://openalex.org/W2768490449","https://openalex.org/W2769533173","https://openalex.org/W2804331675","https://openalex.org/W2860192827","https://openalex.org/W2891398396","https://openalex.org/W2903262661","https://openalex.org/W2904107098","https://openalex.org/W2906587988","https://openalex.org/W2911964244","https://openalex.org/W2950056962","https://openalex.org/W2950095536","https://openalex.org/W2955219541","https://openalex.org/W4211085285","https://openalex.org/W4248107770","https://openalex.org/W4294216483","https://openalex.org/W6675354045","https://openalex.org/W6724984643","https://openalex.org/W6764644684"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W4372048956","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2889302474","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Abstract":[0],"Motivation":[1],"Understanding":[2],"the":[3,27,107,117,143,167,176,190,197],"mechanisms":[4],"and":[5,10,181,205],"structural":[6],"mappings":[7],"between":[8],"molecules":[9],"pathway":[11,120,154,177],"classes":[12,32],"are":[13,100],"critical":[14],"for":[15,20,84,159],"design":[16],"of":[17,29,31,33,37,59,103,114,122,124,134,145,147,170,192],"reaction":[18],"predictors":[19],"synthesizing":[21],"new":[22],"molecules.":[23,108],"This":[24],"article":[25],"studies":[26],"problem":[28,180],"prediction":[30,157,179],"metabolic":[34,119],"pathways":[35],"(series":[36],"chemical":[38,104],"reactions":[39],"occurring":[40],"within":[41],"a":[42,46,53,72],"cell)":[43],"in":[44,152],"which":[45,99],"given":[47],"biochemical":[48],"compound":[49],"participates.":[50],"We":[51,165],"apply":[52],"hybrid":[54],"machine":[55,81],"learning":[56,82],"approach":[57],"consisting":[58],"graph":[60],"convolutional":[61],"networks":[62],"used":[63],"to":[64,71,78,142,175],"extract":[65],"molecular":[66],"shape":[67,92,198],"features":[68,93,174,195,199],"as":[69],"input":[70,96],"random":[73],"forest":[74],"classifier.":[75],"In":[76],"contrast":[77],"previously":[79],"applied":[80],"methods":[83,129],"this":[85,160],"problem,":[86],"our":[87,139,202],"framework":[88,140],"automatically":[89],"extracts":[90],"relevant":[91],"directly":[94],"from":[95,196],"SMILES":[97],"representations,":[98],"atom-bond":[101],"specifications":[102],"structures":[105],"composing":[106],"Results":[109],"Our":[110,156],"method":[111],"is":[112,163],"capable":[113],"correctly":[115],"predicting":[116],"respective":[118],"class":[121,178],"95.16%":[123],"tested":[125],"compounds,":[126],"whereas":[127],"competing":[128],"only":[130],"achieve":[131],"an":[132],"accuracy":[133,158],"84.92%":[135],"or":[136],"less.":[137],"Furthermore,":[138],"extends":[141],"task":[144,162],"classification":[146],"compounds":[148],"having":[149],"mixed":[150],"membership":[151],"multiple":[153],"classes.":[155],"multi-label":[161],"95.62%.":[164],"analyze":[166],"relative":[168],"importance":[169],"various":[171],"global":[172,194],"physicochemical":[173],"show":[182],"that":[183],"simple":[184],"linear/logistic":[185],"regression":[186],"models":[187],"can":[188],"predict":[189],"values":[191],"these":[193],"extracted":[200],"using":[201],"framework.":[203],"Availability":[204],"implementation":[206],"https://github.com/baranwa2/MetabolicPathwayPrediction.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
