{"id":"https://openalex.org/W7126081207","doi":"https://doi.org/10.1109/bibm66473.2025.11357112","title":"AmpLyze: A Deep Learning Model for Predicting the Hemolytic Concentration","display_name":"AmpLyze: A Deep Learning Model for Predicting the Hemolytic Concentration","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126081207","doi":"https://doi.org/10.1109/bibm66473.2025.11357112"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5103015091","display_name":"Peng Qiu","orcid":"https://orcid.org/0000-0002-5886-6021"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Peng Qiu","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University,Pittsburgh,USA,PA 15213"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University,Pittsburgh,USA,PA 15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036879325","display_name":"Hanqi Feng","orcid":"https://orcid.org/0000-0003-1939-2692"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanqi Feng","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University,Pittsburgh,USA,PA 15213"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University,Pittsburgh,USA,PA 15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047335868","display_name":"Meng-Chun Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Meng-Chun Zhang","raw_affiliation_strings":["University of Pittsburgh,Department of Biostatistics,Pittsburgh,USA,PA 15261"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Department of Biostatistics,Pittsburgh,USA,PA 15261","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124263099","display_name":"Barnabas Poczos","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Barnabas Poczos","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University,Pittsburgh,USA,PA 15213"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University,Pittsburgh,USA,PA 15213","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103015091"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72911845,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"172","last_page":"177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11103","display_name":"Antimicrobial Peptides and Activities","score":0.7473000288009644,"subfield":{"id":"https://openalex.org/subfields/2404","display_name":"Microbiology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11103","display_name":"Antimicrobial Peptides and Activities","score":0.7473000288009644,"subfield":{"id":"https://openalex.org/subfields/2404","display_name":"Microbiology"},"field":{"id":"https://openalex.org/fields/24","display_name":"Immunology and Microbiology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.15809999406337738,"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/T12576","display_name":"vaccines and immunoinformatics approaches","score":0.02969999983906746,"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":0.7422000169754028},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6653000116348267},{"id":"https://openalex.org/keywords/in-silico","display_name":"In silico","score":0.660099983215332},{"id":"https://openalex.org/keywords/hemolysis","display_name":"Hemolysis","score":0.5256999731063843},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.4715000092983246},{"id":"https://openalex.org/keywords/toxicity","display_name":"Toxicity","score":0.34049999713897705},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.3321000039577484},{"id":"https://openalex.org/keywords/acute-toxicity","display_name":"Acute toxicity","score":0.3264000117778778}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7422000169754028},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6653000116348267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6607999801635742},{"id":"https://openalex.org/C2775905019","wikidata":"https://www.wikidata.org/wiki/Q192572","display_name":"In silico","level":3,"score":0.660099983215332},{"id":"https://openalex.org/C2779902561","wikidata":"https://www.wikidata.org/wiki/Q471706","display_name":"Hemolysis","level":2,"score":0.5256999731063843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4805000126361847},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44780001044273376},{"id":"https://openalex.org/C29730261","wikidata":"https://www.wikidata.org/wiki/Q274160","display_name":"Toxicity","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3321000039577484},{"id":"https://openalex.org/C116263406","wikidata":"https://www.wikidata.org/wiki/Q3299024","display_name":"Acute toxicity","level":3,"score":0.3264000117778778},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C2779281246","wikidata":"https://www.wikidata.org/wiki/Q172847","display_name":"Peptide","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2766999900341034},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C3019813237","wikidata":"https://www.wikidata.org/wiki/Q65089264","display_name":"Model validation","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25850000977516174},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2080614447","https://openalex.org/W2160780417","https://openalex.org/W2322177339","https://openalex.org/W2322844633","https://openalex.org/W2344689512","https://openalex.org/W2566553664","https://openalex.org/W3047157985","https://openalex.org/W3091899249","https://openalex.org/W3097405028","https://openalex.org/W3161940697","https://openalex.org/W3171209108","https://openalex.org/W3177500196","https://openalex.org/W4255462926","https://openalex.org/W4281949794","https://openalex.org/W4295808856","https://openalex.org/W4319159815","https://openalex.org/W4387140160","https://openalex.org/W4389725105","https://openalex.org/W4399917261","https://openalex.org/W4400026633","https://openalex.org/W4407127289","https://openalex.org/W4408433527"],"related_works":[],"abstract_inverted_index":{"In":[0],"antimicrobial":[1],"peptide":[2],"development,":[3],"red-blood-cell":[4],"lysis":[5],"(<tex":[6],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[7,41,118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\text{HC}_{50}$</tex>)":[8],"is":[9],"the":[10,38,50,103],"principal":[11],"safety":[12],"barrier,":[13],"but":[14],"existing":[15],"in":[16,64],"silico":[17],"tools":[18],"stop":[19],"at":[20],"a":[21,28,72,90,115,141,153],"binary":[22],"toxicity":[23,130,158],"classification.":[24],"Here":[25],"we":[26],"propose":[27],"new":[29],"method,":[30],"AmpLyze,":[31],"that":[32,52,107],"closes":[33],"this":[34],"gap":[35],"by":[36,71],"predicting":[37],"actual":[39],"<tex":[40,117],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\text{HC}_{50}$</tex>":[42],"value":[43],"from":[44],"protein":[45],"sequence":[46],"alone":[47],"and":[48,67,75,94,102,112,122,132,144,151],"explaining":[49],"residues":[51],"drive":[53],"toxicity.":[54],"The":[55,85],"model":[56,88],"couples":[57],"residue-level":[58],"ProtT5/ESM2":[59],"embeddings":[60],"with":[61,77],"sequence-level":[62],"descriptors":[63],"dual":[65],"local":[66],"global":[68],"branches,":[69],"aligned":[70],"cross-attention":[73,113],"module":[74],"trained":[76],"log-cosh":[78],"loss":[79],"for":[80,156],"robustness":[81],"to":[82],"assay":[83],"noise.":[84],"optimal":[86],"AmpLyze":[87,147],"reaches":[89],"PCC":[91],"of":[92,97],"0.756":[93],"an":[95],"MSE":[96,124],"0.987,":[98],"outperforming":[99],"classical":[100],"regressors":[101],"state-of-the-art.":[104],"Ablations":[105],"confirm":[106],"both":[108],"branches":[109],"are":[110],"essential,":[111],"adds":[114],"further":[116],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$1":[119],"\\%":[120],"\\text{PCC}$</tex>":[121],"3%":[123],"improvement.":[125],"Expected-Gradients":[126],"attributions":[127],"reveal":[128],"known":[129],"hotspots":[131],"suggest":[133],"safer":[134],"substitutions.":[135],"By":[136],"turning":[137],"hemolysis":[138],"assessment":[139],"into":[140],"quantitative,":[142],"sequence-based,":[143],"interpretable":[145],"prediction,":[146],"facilitates":[148],"AMP":[149],"design":[150],"offers":[152],"practical":[154],"tool":[155],"early-stage":[157],"screening.":[159]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}