{"id":"https://openalex.org/W4414736102","doi":"https://doi.org/10.1021/acs.jcim.5c01518","title":"The Black Hole Strategy: Gravity-Based Representative Sampling for Frugal Graph Learning on Metal\u2013Organic Framework Networks","display_name":"The Black Hole Strategy: Gravity-Based Representative Sampling for Frugal Graph Learning on Metal\u2013Organic Framework Networks","publication_year":2025,"publication_date":"2025-10-01","ids":{"openalex":"https://openalex.org/W4414736102","doi":"https://doi.org/10.1021/acs.jcim.5c01518","pmid":"https://pubmed.ncbi.nlm.nih.gov/41031749"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.5c01518","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.5c01518","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/A5002207845","display_name":"Mehrdad Jalali","orcid":"https://orcid.org/0000-0003-2465-4933"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]},{"id":"https://openalex.org/I4210091948","display_name":"SRH Hochschule Heidelberg","ror":"https://ror.org/00g07sz63","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210091948"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Mehrdad Jalali","raw_affiliation_strings":["Department of Information","Institute of Functional Interfaces (IFG)","Karlsruhe Institute of Technology (KIT)","SRH University of Applied Sciences Heidelberg"],"raw_orcid":"https://orcid.org/0000-0003-2465-4933","affiliations":[{"raw_affiliation_string":"Department of Information","institution_ids":[]},{"raw_affiliation_string":"Institute of Functional Interfaces (IFG)","institution_ids":[]},{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT)","institution_ids":["https://openalex.org/I102335020"]},{"raw_affiliation_string":"SRH University of Applied Sciences Heidelberg","institution_ids":["https://openalex.org/I4210091948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075970032","display_name":"A. D. Dinga Wonanke","orcid":"https://orcid.org/0000-0002-9066-2715"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"A. D. Dinga Wonanke","raw_affiliation_strings":["Faculty of Chemistry and Food Chemistry","TU Dresden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Chemistry and Food Chemistry","institution_ids":[]},{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052771582","display_name":"Pascal Friederich","orcid":"https://orcid.org/0000-0003-4465-1465"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]},{"id":"https://openalex.org/I4210122744","display_name":"Institute of Theoretical and Applied Informatics","ror":"https://ror.org/037p52j25","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210122744","https://openalex.org/I99542240"]}],"countries":["DE","PL"],"is_corresponding":false,"raw_author_name":"Pascal Friederich","raw_affiliation_strings":["Institute of Nanotechnology","Institute of Theoretical Informatics","Karlsruhe Institute of Technology (KIT)"],"raw_orcid":"https://orcid.org/0000-0003-4465-1465","affiliations":[{"raw_affiliation_string":"Institute of Nanotechnology","institution_ids":[]},{"raw_affiliation_string":"Institute of Theoretical Informatics","institution_ids":["https://openalex.org/I4210122744"]},{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT)","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064307923","display_name":"Christof W\u00f6ll","orcid":"https://orcid.org/0000-0003-1078-3304"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christof W\u00f6ll","raw_affiliation_strings":["Institute of Functional Interfaces (IFG)","Karlsruhe Institute of Technology (KIT)"],"raw_orcid":"https://orcid.org/0000-0003-1078-3304","affiliations":[{"raw_affiliation_string":"Institute of Functional Interfaces (IFG)","institution_ids":[]},{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT)","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002207845","https://openalex.org/A5075970032"],"corresponding_institution_ids":["https://openalex.org/I102335020","https://openalex.org/I4210091948","https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":3.5968,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93222916,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"65","issue":"20","first_page":"10885","last_page":"10902"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10096","display_name":"Metal-Organic Frameworks: Synthesis and Applications","score":0.9595999717712402,"subfield":{"id":"https://openalex.org/subfields/1604","display_name":"Inorganic Chemistry"},"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/T10207","display_name":"Advanced biosensing and bioanalysis techniques","score":0.9210000038146973,"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/leverage","display_name":"Leverage (statistics)","score":0.6215999722480774},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5860999822616577},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5041000247001648},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4814999997615814},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4318000078201294},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4269999861717224},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.38179999589920044},{"id":"https://openalex.org/keywords/interoperability","display_name":"Interoperability","score":0.375},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.366100013256073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6987000107765198},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6215999722480774},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5860999822616577},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5070000290870667},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5041000247001648},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4699000120162964},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4318000078201294},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4309999942779541},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4104999899864197},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.375},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3276999890804291},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32010000944137573},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.27649998664855957},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C50341732","wikidata":"https://www.wikidata.org/wiki/Q880302","display_name":"Black hole (networking)","level":5,"score":0.26570001244544983},{"id":"https://openalex.org/C2987015589","wikidata":"https://www.wikidata.org/wiki/Q1040098","display_name":"Learning network","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.2547000050544739}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000073396","descriptor_name":"Metal-Organic Frameworks","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D000073396","descriptor_name":"Metal-Organic Frameworks","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D006112","descriptor_name":"Gravitation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006112","descriptor_name":"Gravitation","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":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.5c01518","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.5c01518","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:41031749","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41031749","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/G1026715455","display_name":null,"funder_award_id":"101107360","funder_id":"https://openalex.org/F4320338337","funder_display_name":"H2020 Marie Sk\u0142odowska-Curie Actions"},{"id":"https://openalex.org/G2931761144","display_name":"FAIRmat \u2013 FAIRe Dateninfrastruktur f\u00fcr die Physik der kondensierten Materie und die chemische Physik fester Stoffe","funder_award_id":"460197019","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320338337","display_name":"H2020 Marie Sk\u0142odowska-Curie Actions","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1970065157","https://openalex.org/W2138085558","https://openalex.org/W2141939342","https://openalex.org/W2146008005","https://openalex.org/W2319902168","https://openalex.org/W2592285292","https://openalex.org/W2599075544","https://openalex.org/W2884430236","https://openalex.org/W2968923792","https://openalex.org/W2983028326","https://openalex.org/W3000754666","https://openalex.org/W3102096994","https://openalex.org/W3158461739","https://openalex.org/W3174154718","https://openalex.org/W4214674586","https://openalex.org/W4223910234","https://openalex.org/W4224101701","https://openalex.org/W4286252241","https://openalex.org/W4290997390","https://openalex.org/W4304184517","https://openalex.org/W4317565709","https://openalex.org/W4382931980","https://openalex.org/W4386718372","https://openalex.org/W4387542153","https://openalex.org/W4390451371","https://openalex.org/W4391561379","https://openalex.org/W4391982072","https://openalex.org/W4392281897","https://openalex.org/W4406794969","https://openalex.org/W4408595679","https://openalex.org/W4409821965","https://openalex.org/W4413076584"],"related_works":[],"abstract_inverted_index":{"The":[0],"expansion":[1],"of":[2,10,128,157,210],"large-scale":[3],"materials":[4,70,194,227,251],"databases":[5],"has":[6],"facilitated":[7],"the":[8,54,152,158,167,180,208,211],"development":[9],"graph-based":[11],"representations,":[12],"encoding":[13],"structural":[14,75],"and":[15,33,43,76,95,107,120,123,155,161,172,187,199,226,248],"functional":[16],"similarities":[17],"as":[18,83,137,184],"edges":[19],"in":[20,193,250],"data-driven":[21],"networks.":[22],"These":[23,177],"enable":[24],"machine":[25,191],"learning":[26,192],"models":[27],"to":[28,111,207,216],"leverage":[29],"both":[30],"local":[31],"features":[32],"global":[34],"relationships.":[35],"However,":[36],"densely":[37],"connected":[38],"datasets":[39,71,101],"often":[40],"introduce":[41,53],"redundancy":[42],"noise,":[44],"escalating":[45],"computational":[46],"complexity":[47],"without":[48],"improving":[49],"performance.":[50],"Here,":[51],"we":[52,87],"Black":[55,99,181],"Hole":[56,182],"Strategy,":[57],"a":[58,84,185,218],"gravity-based":[59],"representative":[60],"sampling":[61,241],"method":[62,168],"that":[63,89,133,166,243],"constructs":[64],"compact,":[65],"informative":[66],"subsets":[67],"from":[68],"large":[69],"while":[72],"preserving":[73],"essential":[74],"property":[77],"diversity.":[78],"Using":[79],"metal-organic":[80],"frameworks":[81],"(MOFs)":[82],"case":[85],"study,":[86],"demonstrate":[88,165],"graph":[90],"neural":[91],"networks":[92],"(GraphSAGE,":[93],"GCN,":[94],"GAT)":[96],"trained":[97],"on":[98,147],"Hole-sparsified":[100],"achieve":[102],"comparable":[103],"or":[104],"superior":[105],"classification":[106],"regression":[108],"performance":[109],"compared":[110],"full-dataset":[112],"models,":[113],"despite":[114],"utilizing":[115],"significantly":[116],"fewer":[117],"data":[118,220,237,245],"points":[119],"reduced":[121],"memory":[122],"training":[124],"time":[125],"requirements.":[126],"Analysis":[127],"class-level":[129],"confusion":[130],"matrices":[131],"confirms":[132],"critical":[134],"structure-property":[135],"relationships\u2500such":[136],"pore-limiting":[138],"diameter":[139],"(PLD)\u2500persist":[140],"under":[141],"substantial":[142],"sparsification.":[143],"An":[144],"ablation":[145],"study":[146],"gravity":[148],"score":[149],"weights":[150],"validates":[151],"balanced":[153],"formulation":[154],"robustness":[156],"approach.":[159],"Topological":[160],"efficiency":[162],"benchmarks":[163],"further":[164],"preserves":[169],"modularity,":[170],"diversity,":[171],"connectivity":[173],"across":[174],"sparsification":[175],"levels.":[176],"findings":[178],"establish":[179],"Strategy":[183],"principled":[186],"frugal":[188],"approach":[189,230],"for":[190,222],"science,":[195],"enabling":[196],"efficient,":[197],"interpretable,":[198],"scalable":[200],"discovery":[201],"workflows.":[202],"Importantly,":[203],"this":[204],"work":[205],"contributes":[206],"objectives":[209],"FAIRmat":[212],"consortium,":[213],"which":[214],"aims":[215],"develop":[217],"FAIR":[219,232],"infrastructure":[221],"condensed":[223],"matter":[224],"physics":[225],"science.":[228],"Our":[229],"advances":[231],"(Findable,":[233],"Accessible,":[234],"Interoperable,":[235],"Reusable)":[236],"practices":[238],"through":[239],"optimized":[240],"techniques":[242],"enhance":[244],"management,":[246],"reusability,":[247],"interoperability":[249],"informatics.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}