{"id":"https://openalex.org/W4402351911","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650775","title":"CyclePermea: Membrane Permeability Prediction of Cyclic Peptides with a Multi-Loss Fusion Network","display_name":"CyclePermea: Membrane Permeability Prediction of Cyclic Peptides with a Multi-Loss Fusion Network","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351911","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650775"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5100690879","display_name":"Zixu Wang","orcid":"https://orcid.org/0000-0002-6809-4088"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Zixu Wang","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760185","display_name":"Yangyang Chen","orcid":"https://orcid.org/0000-0002-3521-475X"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yangyang Chen","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072571384","display_name":"Xiucai Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiucai Ye","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080813451","display_name":"Tetsuya Sakurai","orcid":"https://orcid.org/0000-0003-2046-8973"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Sakurai","raw_affiliation_strings":["University of Tsukuba,Department of Computer Science,Tsukuba,Japan"],"affiliations":[{"raw_affiliation_string":"University of Tsukuba,Department of Computer Science,Tsukuba,Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100690879"],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":1.5003,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82350009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10911","display_name":"Chemical Synthesis and Analysis","score":0.9991999864578247,"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/T10911","display_name":"Chemical Synthesis and Analysis","score":0.9991999864578247,"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":0.9984999895095825,"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/T10521","display_name":"RNA and protein synthesis mechanisms","score":0.9980000257492065,"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/fusion","display_name":"Fusion","score":0.6270004510879517},{"id":"https://openalex.org/keywords/permeability","display_name":"Permeability (electromagnetism)","score":0.5978876352310181},{"id":"https://openalex.org/keywords/membrane","display_name":"Membrane","score":0.49527469277381897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4400591552257538},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.37690553069114685},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.31015443801879883},{"id":"https://openalex.org/keywords/biochemistry","display_name":"Biochemistry","score":0.07894629240036011}],"concepts":[{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6270004510879517},{"id":"https://openalex.org/C120882062","wikidata":"https://www.wikidata.org/wiki/Q28352","display_name":"Permeability (electromagnetism)","level":3,"score":0.5978876352310181},{"id":"https://openalex.org/C41625074","wikidata":"https://www.wikidata.org/wiki/Q176088","display_name":"Membrane","level":2,"score":0.49527469277381897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4400591552257538},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.37690553069114685},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.31015443801879883},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.07894629240036011},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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":39,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W2004926660","https://openalex.org/W2065601090","https://openalex.org/W2075613930","https://openalex.org/W2123196322","https://openalex.org/W2136359146","https://openalex.org/W2896457183","https://openalex.org/W2899070097","https://openalex.org/W2900679761","https://openalex.org/W2942566598","https://openalex.org/W2963477629","https://openalex.org/W2964015378","https://openalex.org/W2970641574","https://openalex.org/W2982145560","https://openalex.org/W3019745511","https://openalex.org/W3093934881","https://openalex.org/W3094744425","https://openalex.org/W3113831423","https://openalex.org/W3146944767","https://openalex.org/W3164445425","https://openalex.org/W3215795311","https://openalex.org/W4206722897","https://openalex.org/W4210690417","https://openalex.org/W4297733535","https://openalex.org/W4313236104","https://openalex.org/W4327694659","https://openalex.org/W4361218849","https://openalex.org/W4366462849","https://openalex.org/W4382516982","https://openalex.org/W4385245566","https://openalex.org/W4387440466","https://openalex.org/W4387865628","https://openalex.org/W4394715402","https://openalex.org/W4402076677","https://openalex.org/W6726873649","https://openalex.org/W6755207826","https://openalex.org/W6774314701","https://openalex.org/W6784526300","https://openalex.org/W6857055631"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W2748952813","https://openalex.org/W1531601525","https://openalex.org/W4391375266","https://openalex.org/W2078814861","https://openalex.org/W2527526854","https://openalex.org/W1976181487","https://openalex.org/W1986764834"],"abstract_inverted_index":{"Cyclic":[0],"peptides,":[1,58,75],"known":[2],"for":[3],"their":[4,16],"unique":[5,147],"ring-like":[6],"structures,":[7],"show":[8],"considerable":[9],"promise":[10],"in":[11,151,164,169,182,191],"therapeutic":[12],"applications.":[13],"Experimentally":[14],"determining":[15],"permeability":[17,28,55,66],"is":[18,138],"time-consuming":[19],"and":[20,25,84,172],"labor-intensive.":[21],"Hence,":[22],"an":[23],"efficient":[24],"rapid":[26],"membrane":[27,54,65],"prediction":[29],"model":[30,51],"would":[31,180],"greatly":[32],"expedite":[33],"the":[34,69,109,127,142,146,165,184,192],"early-stage":[35],"screening":[36,186],"of":[37,56,73,112,129,145,187],"cyclic":[38,57,74,113,152,188],"peptide":[39,91,189],"drugs.":[40],"To":[41],"meet":[42],"this":[43],"end,":[44],"we":[45],"proposed":[46,139],"a":[47,90,95],"novel":[48],"deep":[49],"learning":[50],"to":[52,107,125,140],"predict":[53],"dubbed":[59],"as":[60],"CyclePermea.":[61],"Remarkably,":[62],"CyclePermea":[63,157,179],"predicts":[64],"using":[67],"only":[68],"1D":[70],"sequence":[71],"information":[72],"unlike":[76],"previous":[77],"works":[78],"based":[79,93],"on":[80,94],"complex":[81],"spatial":[82,148],"descriptors":[83],"various":[85],"physicochemical":[86],"properties.":[87],"It":[88],"incorporates":[89],"encoder":[92],"pre-trained":[96],"BERT":[97],"architecture.":[98],"We":[99,176],"also":[100],"introduced":[101],"two":[102],"auxiliary":[103],"loss":[104],"functions":[105],"designed":[106],"enhance":[108],"model\u2019s":[110,143],"comprehension":[111],"peptides\u2019":[114],"distinctive":[115],"characteristics.":[116],"The":[117,132],"first,":[118],"termed":[119],"\u2019Constraint":[120],"Contrastive":[121],"Learning":[122],"Loss\u2019,":[123,137],"aims":[124],"mitigate":[126],"challenge":[128],"feature":[130],"clustering.":[131],"second,":[133],"\u2019Cyclization":[134],"Site":[135],"Prediction":[136],"facilitate":[141],"recognition":[144],"structure":[149],"inherent":[150],"peptides.":[153],"Through":[154],"extensive":[155],"experiments,":[156],"demonstrated":[158],"superior":[159],"performance":[160],"over":[161],"baseline":[162],"models":[163],"benchmark":[166],"dataset,":[167],"both":[168],"in-distribution":[170],"settings":[171],"simulated":[173],"out-of-distribution":[174],"settings.":[175],"hope":[177],"that":[178],"contribute":[181],"accelerating":[183],"early":[185],"drugs":[190],"future.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
