{"id":"https://openalex.org/W7130528963","doi":"https://doi.org/10.6084/m9.figshare.31362145","title":"Supporting Data for Zhao et al. \"Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks\"","display_name":"Supporting Data for Zhao et al. \"Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks\"","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7130528963","doi":"https://doi.org/10.6084/m9.figshare.31362145"},"language":"en","primary_location":{"id":"doi:10.6084/m9.figshare.31362145","doi":"https://doi.org/10.6084/m9.figshare.31362145","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.31362145","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"volume":null,"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.6084/m9.figshare.31362145","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126373996","display_name":"Haiqing Zhao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Haiqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051722239","display_name":"Caroline Velez","orcid":"https://orcid.org/0000-0003-3491-9835","observed_orcids":["https://orcid.org/0000-0003-3491-9835"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"velez, caroline","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092974658","display_name":"Aniket C. Naravane","orcid":"https://orcid.org/0000-0001-6196-8400","observed_orcids":["https://orcid.org/0000-0001-6196-8400"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naravane, Aniket","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003328243","display_name":"Aakash Saha","orcid":"https://orcid.org/0000-0003-0776-9771","observed_orcids":["https://orcid.org/0000-0003-0776-9771"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saha, Aakash","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0776-9771","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126400852","display_name":"Jonathan Feldman","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feldman, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010808261","display_name":"Jeffrey Skolnick","orcid":"https://orcid.org/0000-0002-1877-4958","observed_orcids":["https://orcid.org/0000-0002-1877-4958"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Skolnick, Jeffrey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081710529","display_name":"Diana Murray","orcid":"https://orcid.org/0000-0003-4121-1536","observed_orcids":["https://orcid.org/0000-0003-4121-1536"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Murray, Diana","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4121-1536","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036654109","display_name":"Barry H. Honig","orcid":"https://orcid.org/0000-0002-1835-1031","observed_orcids":["https://orcid.org/0000-0002-1835-1031","https://orcid.org/0000-0002-2480-6696"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Honig, Barry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9824000000953674,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9824000000953674,"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":0.005400000140070915,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.004900000058114529,"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/protein-protein-interaction-prediction","display_name":"protein-protein interaction prediction","score":0.9210000038146973},{"id":"https://openalex.org/keywords/protein-complex-structure-prediction","display_name":"protein complex structure prediction","score":0.593999981880188},{"id":"https://openalex.org/keywords/protein-language-models","display_name":"protein language models","score":0.671999990940094},{"id":"https://openalex.org/keywords/protein-protein-interface-prediction","display_name":"protein-protein interface prediction","score":0.6620000004768372},{"id":"https://openalex.org/keywords/evolutionary-information","display_name":"evolutionary information","score":0.5049999952316284},{"id":"https://openalex.org/keywords/bayesian-integration","display_name":"Bayesian integration","score":0.43799999356269836},{"id":"https://openalex.org/keywords/functional-networks","display_name":"functional networks","score":0.6549999713897705},{"id":"https://openalex.org/keywords/protein-function-annotation","display_name":"protein annotation","score":0.5889999866485596},{"id":"https://openalex.org/keywords/topsy-turvy","display_name":"topsy-turvy","score":0.9350000023841858}],"concepts":[{"id":"https://openalex.org/C9760119","wikidata":"https://www.wikidata.org/wiki/Q841382","display_name":"Interactome","level":3,"score":0.8833000063896179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6744999885559082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857999920845032},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.447299987077713},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C11804247","wikidata":"https://www.wikidata.org/wiki/Q896177","display_name":"Protein\u2013protein interaction","level":2,"score":0.42590001225471497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.414900004863739},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.39820000529289246},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C2777683733","wikidata":"https://www.wikidata.org/wiki/Q201456","display_name":"Directory","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.35690000653266907},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C38764148","wikidata":"https://www.wikidata.org/wiki/Q17098245","display_name":"Interaction information","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.2957000136375427},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.28110000491142273},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C20901353","wikidata":"https://www.wikidata.org/wiki/Q4117139","display_name":"Biological database","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C10010492","wikidata":"https://www.wikidata.org/wiki/Q3142557","display_name":"Protein sequencing","level":4,"score":0.2718000113964081},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25049999356269836},{"id":"https://openalex.org/C7952369","wikidata":"https://www.wikidata.org/wiki/Q844116","display_name":"Phenome","level":4,"score":0.25040000677108765},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.6084/m9.figshare.31362145","doi":"https://doi.org/10.6084/m9.figshare.31362145","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.31362145","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},{"id":"doi:10.6084/m9.figshare.31362145.v1","doi":"https://doi.org/10.6084/m9.figshare.31362145.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.31362145.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.6084/m9.figshare.31362145","doi":"https://doi.org/10.6084/m9.figshare.31362145","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.31362145","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4410287065","https://openalex.org/W4394513398","https://openalex.org/W2856525285","https://openalex.org/W4393779971","https://openalex.org/W6965033378","https://openalex.org/W7164557288","https://openalex.org/W4415590382","https://openalex.org/W7131794015","https://openalex.org/W4393502669","https://openalex.org/W7125782122"],"abstract_inverted_index":{"SupportingData":[0,166],"Directory":[1],"for":[2,57,359,373,410],"Zhao":[3,227],"et":[4,228],"al.":[5],"\"Combining":[6],"structural":[7,451],"modeling":[8,466],"and":[9,19,66,93,204,271,301,309,324,343,362,396,417,483,498],"deep":[10],"learning":[11],"to":[12,40,72,109,285,386],"calculate":[13],"the":[14,24,78,87,101,111,130,135,152,155,182,205,215,248,261,265,287,325,338,344,379,390,464,478,484,499],"E.":[15,137,187,411],"coli":[16,138,188,412],"protein":[17,63,249],"interactome":[18,139,276],"functional":[20,146,272],"networks\"AbstractWe":[21],"report":[22],"on":[23,31,77,432],"integration":[25],"of":[26,82,100,113,129,134,157,159,186,264,392,458],"three":[27,194],"methods":[28,46],"that":[29,86],"predict,":[30],"a":[32,42,55,62,117,428],"proteome-wide":[33],"scale,":[34],"whether":[35],"two":[36],"proteins":[37,158],"are":[38,162,244,258,321,337,425,455,477,495],"likely":[39],"form":[41],"binary":[43,83,354],"complex.":[44,132],"The":[45,104,290,436],"include":[47],"PrePPI,":[48,200],"which":[49,60,68,143,192],"uses":[50,61,69],"three-dimensional":[51],"structure":[52],"information":[53,71],"as":[54,389],"basis":[56],"predictions,":[58],"Topsy-Turvy,":[59],"language":[64,443],"model,":[65],"ZEPPI,":[67,201,300,416],"evolutionary":[70],"evaluate":[73],"protein-protein":[74],"interfaces.":[75],"Testing":[76],"high-quality":[79,353],"HINT":[80,308,350],"database":[81],"PPIs":[84,115,235,306,393],"reveals":[85],"integrated":[88,170,184,206,239,426,437],"method":[89],"has":[90],"better":[91],"performance":[92],"identifies":[94],"more":[95],"high-confidence":[96,136,238],"interactions":[97,190,243],"than":[98],"any":[99],"component":[102],"methods.":[103],"AF3Complex":[105],"algorithm":[106],"was":[107],"used":[108,284,333,358,372,473],"predict":[110],"structures":[112],"374":[114,233],"with":[116,126,237],"large":[118],"fraction":[119],"having":[120],"at":[121],"least":[122],"partially":[123],"overlapping":[124],"interfaces":[125],"PrePPI":[127,450],"models":[128],"same":[131],"Clustering":[133],"yields":[140],"385":[141],"subnetworks":[142],"have":[144],"high":[145],"coherence.":[147],"Biological":[148],"insights":[149],"derived":[150,198],"from":[151,275,307,316,329,349,364,449,469,490],"subnetworks,":[153],"including":[154],"annotation":[156,273],"unknown":[160],"function,":[161],"discussed":[163],"in":[164,226,260,312,334,474],"detail.ContentsThe":[165],"directory":[167],"contains:One":[168],"final":[169,183],"prediction":[171,185,196,207],"fileThree":[172],"main":[173],"subfolders:SI":[174],"TablesTrainingData_Human-PPI-InteractomesTestData_Ecoli-PPI-Interactomes1.":[175],"Final":[176],"Integrated":[177],"Prediction":[178],"Fileecoli_PPIs_LRINT_threeclues.csvThis":[179],"file":[180,448],"contains":[181,222,282,406],"protein\u2013protein":[189],"(PPIs),":[191],"includes":[193],"individual":[195],"clues":[197],"from:":[199],"D-Script":[202,302,317,418,491],"(TT),":[203],"score":[208,438],"INTLR":[209],"(Integrated":[210],"Likelihood":[211],"Ratio)":[212],"generated":[213,297,413],"by":[214,298,414],"Bayesian":[216,288,429],"model.2.":[217],"SI":[218],"Tables":[219],"FolderThis":[220,280,404],"folder":[221,281,405],"supplemental":[223],"tables":[224],"referenced":[225],"al.,":[229],"2025":[230],"(https://www.biorxiv.org/content/10.1101/2025.05.07.652715v1)Table":[231],"S1Contains":[232],"selected":[234],"predicted":[236],"likelihood":[240,467],"ratio":[241],"(LR).These":[242],"considered":[245],"challenging":[246],"because":[247],"pairs":[250],"exhibit":[251],"low":[252],"local":[253],"sequence":[254],"identity.Detailed":[255],"selection":[256],"criteria":[257],"described":[259],"Methods":[262],"section":[263],"paper.Table":[266],"S2Contains":[267],"network":[268],"construction,":[269],"clustering,":[270],"results.Derived":[274],"clustering":[277],"analysis.3.":[278],"TrainingData_Human-PPI-Interactomes":[279],"datasets":[283,292],"train":[286],"model.":[289],"training":[291],"include:Genome-wide":[293],"human":[294,305,382,433],"PPI":[295,369,384,408,434],"predictions":[296,409,424],"PrePPI-AF,":[299,415],"(TT).Experimentally":[303],"validated":[304],"STRING":[310,365],"(located":[311],"/ExptDB)Files":[313],"IncludedHuman_TT_all.tsvDefault":[314],"output":[315,489],"(TT,":[318,492],"https://topsyturvy.csail.mit.edu).":[319,493],"Columns":[320,332,357,472,494],"uniprotID1,":[322,496],"uniprotID2,":[323,497],"Predicted":[326,500],"probability":[327,501],"score.Human_ZEPPI_all.csvOutput":[328],"ZEPPI":[330,470],"(https://github.com/honig-lab/ZEPPI).":[331,471],"this":[335,421,475],"work":[336,476],"first":[339,479],"column":[340,346,480,486],"(UniProtID":[341,481],"pair)":[342,482],"last":[345,485],"(ZEPPI":[347,487],"score)./ExptDB/2021HINT_Human_lcb_hq.txtDownloaded":[348],"(2021).":[351],"Literature-curated,":[352],"interaction":[355],"dataset.":[356,370],"training:":[360,374],"UniprotID_A":[361],"UniprotID_B./ExptDB/2022String_9606.physical.links.experimental.sortedpair.nonred.csvDownloaded":[363],"(2022).":[366],"Physical":[367],"experimental":[368,383],"Column":[371,453,461],"UniprotID_A_UniprotID_B./ExptDB/human_allExpDB.csvIn-house":[375],"curated":[376],"dataset":[377,385],"representing":[378],"largest":[380],"compiled":[381],"date.":[387],"Constructed":[388],"union":[391],"from:HINT":[394],"(binary":[395],"co-complex)Interactome3DAPID_level0STRING_allBIOGRID_allHURI_allHigh-confidence":[397],"in-house":[398],"reference":[399],"set":[400],"(PrePPI-total":[401],"2016)4.":[402],"TestData_Ecoli-PPI-Interactomes":[403],"genome-wide":[407],"(TT).":[419],"In":[420],"study,":[422],"these":[423],"using":[427],"model":[430],"trained":[431],"data.":[435],"reflects":[439],"evidence":[440],"from:Structure-based":[441],"modelingProtein":[442],"modelsSequence":[444],"co-evolution":[445],"signalsFiles":[446],"Includedecoli_PrePPI_SM_ns.csvPrediction":[447],"modeling.":[452],"1\u20132":[454],"UniProt":[456],"IDs":[457],"interacting":[459],"proteins.":[460],"3":[462],"is":[463],"Structural":[465],"score.ecoli_ZEPPI_all.csvOutput":[468],"score).ecoliK12_TT_all.tsvDefault":[488],"score.":[502]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-02-20T00:00:00"}