{"id":"https://openalex.org/W7129528793","doi":"https://doi.org/10.1021/acs.jcim.5c02548","title":"IALA-LNN: Deep Learning for Peptide Retention Time Prediction Based on Improved Artificial Lemming Algorithm-Optimized Liquid Neural Networks","display_name":"IALA-LNN: Deep Learning for Peptide Retention Time Prediction Based on Improved Artificial Lemming Algorithm-Optimized Liquid Neural Networks","publication_year":2026,"publication_date":"2026-02-17","ids":{"openalex":"https://openalex.org/W7129528793","doi":"https://doi.org/10.1021/acs.jcim.5c02548","pmid":"https://pubmed.ncbi.nlm.nih.gov/41701342"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.5c02548","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.5c02548","pdf_url":null,"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":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126180120","display_name":"Yu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Yu Chen","raw_affiliation_strings":["Changzhou University","School of Computer Science and Artificial Intelligence Aliyun School of Big Data School of Software"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changzhou University","institution_ids":["https://openalex.org/I4210153482"]},{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence Aliyun School of Big Data School of Software","institution_ids":["https://openalex.org/I4210164862"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110787429","display_name":"Lun Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","CN"],"is_corresponding":true,"raw_author_name":"Lun Zhu","raw_affiliation_strings":["Changzhou University","School of Computer Science and Artificial Intelligence Aliyun School of Big Data School of Software"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changzhou University","institution_ids":["https://openalex.org/I4210153482"]},{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence Aliyun School of Big Data School of Software","institution_ids":["https://openalex.org/I4210164862"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126193397","display_name":"Sen Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153482","display_name":"Changzhou University","ror":"https://ror.org/04ymgwq66","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153482"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","CN"],"is_corresponding":true,"raw_author_name":"Sen Yang","raw_affiliation_strings":["Changzhou University","School of Computer Science and Artificial Intelligence Aliyun School of Big Data School of Software"],"raw_orcid":"https://orcid.org/0000-0003-4177-0653","affiliations":[{"raw_affiliation_string":"Changzhou University","institution_ids":["https://openalex.org/I4210153482"]},{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence Aliyun School of Big Data School of Software","institution_ids":["https://openalex.org/I4210164862"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110787429","https://openalex.org/A5126193397"],"corresponding_institution_ids":["https://openalex.org/I4210153482","https://openalex.org/I4210164862"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26409314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"66","issue":"5","first_page":"2513","last_page":"2533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10519","display_name":"Advanced Proteomics Techniques and Applications","score":0.9316999912261963,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10519","display_name":"Advanced Proteomics Techniques and Applications","score":0.9316999912261963,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.03849999979138374,"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/T10683","display_name":"Mass Spectrometry Techniques and Applications","score":0.008899999782443047,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7289000153541565},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.7225000262260437},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6751000285148621},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5730999708175659},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.41670000553131104},{"id":"https://openalex.org/keywords/biomarker-discovery","display_name":"Biomarker discovery","score":0.40220001339912415},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.37959998846054077},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3677999973297119},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.35899999737739563}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7289000153541565},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7225000262260437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951000094413757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6844000220298767},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6751000285148621},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5730999708175659},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42899999022483826},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C124535831","wikidata":"https://www.wikidata.org/wiki/Q4915074","display_name":"Biomarker discovery","level":4,"score":0.40220001339912415},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.37959998846054077},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.35899999737739563},{"id":"https://openalex.org/C3020018676","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Retention time","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C2779281246","wikidata":"https://www.wikidata.org/wiki/Q172847","display_name":"Peptide","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.31850001215934753},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.31779998540878296},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C10010492","wikidata":"https://www.wikidata.org/wiki/Q3142557","display_name":"Protein sequencing","level":4,"score":0.287200003862381},{"id":"https://openalex.org/C46111723","wikidata":"https://www.wikidata.org/wiki/Q471857","display_name":"Proteomics","level":3,"score":0.2750999927520752},{"id":"https://openalex.org/C111364199","wikidata":"https://www.wikidata.org/wiki/Q2915896","display_name":"Protein methods","level":4,"score":0.27309998869895935},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C167625842","wikidata":"https://www.wikidata.org/wiki/Q899763","display_name":"Peptide sequence","level":3,"score":0.25060001015663147}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002853","descriptor_name":"Chromatography, Liquid","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010455","descriptor_name":"Peptides","qualifier_ui":"Q000032","qualifier_name":"analysis","is_major_topic":true},{"descriptor_ui":"D010455","descriptor_name":"Peptides","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","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":"D040901","descriptor_name":"Proteomics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D053719","descriptor_name":"Tandem Mass Spectrometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.5c02548","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.5c02548","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:41701342","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41701342","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}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3186929182","display_name":null,"funder_award_id":"BK20230626","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G5046590544","display_name":null,"funder_award_id":"62502053","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W2011291072","https://openalex.org/W2015466408","https://openalex.org/W2020373481","https://openalex.org/W2023010129","https://openalex.org/W2033557869","https://openalex.org/W2039058260","https://openalex.org/W2043896568","https://openalex.org/W2043951056","https://openalex.org/W2079843936","https://openalex.org/W2087481305","https://openalex.org/W2095695420","https://openalex.org/W2105167594","https://openalex.org/W2139196828","https://openalex.org/W2162103775","https://openalex.org/W2199791113","https://openalex.org/W2240370503","https://openalex.org/W2275699456","https://openalex.org/W2290883490","https://openalex.org/W2396621135","https://openalex.org/W2467577919","https://openalex.org/W2519691041","https://openalex.org/W2573137292","https://openalex.org/W2887566220","https://openalex.org/W2947763854","https://openalex.org/W2963341956","https://openalex.org/W2995514860","https://openalex.org/W2998913628","https://openalex.org/W2999515666","https://openalex.org/W3014879164","https://openalex.org/W3015750191","https://openalex.org/W3016953559","https://openalex.org/W3033739625","https://openalex.org/W3087184316","https://openalex.org/W3093182664","https://openalex.org/W3093407181","https://openalex.org/W3096541186","https://openalex.org/W3127238141","https://openalex.org/W3146944767","https://openalex.org/W3159027297","https://openalex.org/W3161702043","https://openalex.org/W3164630882","https://openalex.org/W3177500196","https://openalex.org/W3208719333","https://openalex.org/W4296965067","https://openalex.org/W4309471863","https://openalex.org/W4310059354","https://openalex.org/W4323971919","https://openalex.org/W4327550249","https://openalex.org/W4362665748","https://openalex.org/W4362724099","https://openalex.org/W4384564289","https://openalex.org/W4386498759","https://openalex.org/W4389038991","https://openalex.org/W4389117655","https://openalex.org/W4400378009","https://openalex.org/W4401202991","https://openalex.org/W4401645453","https://openalex.org/W4402708087","https://openalex.org/W4403013847","https://openalex.org/W4406080942","https://openalex.org/W4406103548","https://openalex.org/W4411096254","https://openalex.org/W4414067311"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"prediction":[1],"of":[2,91,99,146,154],"peptide":[3,32,180],"retention":[4,36,92,176],"times":[5],"is":[6],"crucial":[7],"for":[8,133],"reliable":[9],"identification":[10,181],"in":[11,31,51],"liquid":[12,62],"chromatography\u2013tandem":[13],"mass":[14],"spectrometry":[15],"(LC\u2013MS/MS)":[16],"proteomics.":[17],"Current":[18],"methods":[19],"using":[20],"static":[21],"neural":[22,63,172],"networks":[23,64,173],"fail":[24],"to":[25,48],"capture":[26],"the":[27,96],"complex":[28,52],"sequential":[29],"dependencies":[30],"structures":[33],"that":[34,60,122,169],"determine":[35],"patterns.":[37],"Moreover,":[38],"conventional":[39],"hyperparameter":[40,134],"optimization":[41],"strategies":[42],"are":[43],"computationally":[44],"inefficient":[45],"and":[46,81,110,130,139,149,157,164,187,195],"prone":[47],"suboptimal":[49],"solutions":[50],"search":[53],"spaces.":[54],"We":[55],"introduce":[56],"IALA-LNN,":[57],"a":[58,124],"framework":[59,104],"employs":[61],"(LNN)":[65],"with":[66,115,151],"state":[67],"evolution":[68],"governed":[69],"by":[70],"ordinary":[71],"differential":[72,170],"equations":[73],"(ODE).":[74],"This":[75],"architecture":[76],"captures":[77],"position-dependent":[78],"sequence":[79,86],"information":[80,84],"progressively":[82],"integrates":[83],"throughout":[85],"processing,":[87],"enabling":[88],"effective":[89],"modeling":[90],"time":[93],"based":[94],"on":[95],"combined":[97],"contributions":[98],"amino":[100],"acid":[101],"residues.":[102],"The":[103],"combines":[105],"dual":[106],"encoding":[107],"via":[108],"ESM-2":[109],"ProtT5":[111],"protein":[112],"language":[113],"models":[114],"an":[116],"improved":[117],"artificial":[118],"lemming":[119],"algorithm":[120],"(IALA)":[121],"features":[123],"multielite":[125],"pool":[126],"guidance,":[127],"gradient-enhanced":[128],"search,":[129],"Goodnode":[131],"initialization":[132],"optimization.":[135],"Across":[136],"RP,":[137],"SCX,":[138],"HILIC":[140],"chromatography,":[141],"IALA-LNN":[142],"achieved":[143],"R2":[144],"values":[145,153],"0.994,":[147],"0.998,":[148,150],"MAE":[152],"0.77,":[155],"0.085,":[156],"0.07":[158],"min,":[159],"substantially":[160],"outperforming":[161],"DeepRT,":[162],"DeepLC,":[163],"Prosit.":[165],"These":[166],"results":[167],"demonstrate":[168],"equation-based":[171],"effectively":[174],"model":[175],"patterns,":[177],"directly":[178],"enhancing":[179],"reliability,":[182],"reducing":[183],"false":[184],"discovery":[185,194],"rates,":[186],"supporting":[188],"precision":[189],"proteomics":[190],"applications,":[191],"including":[192],"biomarker":[193],"targeted":[196],"workflows.":[197]},"counts_by_year":[],"updated_date":"2026-05-16T08:24:45.110214","created_date":"2026-02-18T00:00:00"}