{"id":"https://openalex.org/W4323310840","doi":"https://doi.org/10.1186/s12859-022-05047-5","title":"Gene regulation network inference using k-nearest neighbor-based mutual information estimation: revisiting an old DREAM","display_name":"Gene regulation network inference using k-nearest neighbor-based mutual information estimation: revisiting an old DREAM","publication_year":2023,"publication_date":"2023-03-06","ids":{"openalex":"https://openalex.org/W4323310840","doi":"https://doi.org/10.1186/s12859-022-05047-5","pmid":"https://pubmed.ncbi.nlm.nih.gov/36879188"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-022-05047-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-05047-5","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-05047-5","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-05047-5","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029392337","display_name":"Lior Shachaf","orcid":"https://orcid.org/0000-0001-6827-8605"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lior I. Shachaf","raw_affiliation_strings":["Department of Biophysics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, 21218, USA. lshacha1@jhu.edu","Department of Biophysics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, 21218, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biophysics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, 21218, USA. lshacha1@jhu.edu","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Department of Biophysics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003124534","display_name":"Elijah Roberts","orcid":"https://orcid.org/0000-0002-5619-8066"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I4210117513","display_name":"10X Genomics (United States)","ror":"https://ror.org/01sxvbm95","country_code":"US","type":"company","lineage":["https://openalex.org/I4210117513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elijah Roberts","raw_affiliation_strings":["10x Genomics, 6230 Stoneridge Mall Road, Pleasanton, CA, 94588-3260, USA","Department of Biophysics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, 21218, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"10x Genomics, 6230 Stoneridge Mall Road, Pleasanton, CA, 94588-3260, USA","institution_ids":["https://openalex.org/I4210117513"]},{"raw_affiliation_string":"Department of Biophysics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, 21218, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004108540","display_name":"Patrick Cahan","orcid":"https://orcid.org/0000-0003-3652-2540"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I2799853436","display_name":"Johns Hopkins Medicine","ror":"https://ror.org/037zgn354","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799853436"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patrick Cahan","raw_affiliation_strings":["Department of Biomedical Engineering, Department of Molecular Biology and Genetics, Institute for Cell Engineering, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Department of Molecular Biology and Genetics, Institute for Cell Engineering, Johns Hopkins School of Medicine, 733 N. Broadway, Baltimore, MD, 21205, USA","institution_ids":["https://openalex.org/I145311948","https://openalex.org/I2799853436"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045471152","display_name":"Jie Xiao","orcid":"https://orcid.org/0000-0003-1433-5437"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Xiao","raw_affiliation_strings":["Department of Biophysics and Biophysical Chemistry, Johns Hopkins School of Medicine, 725 N. Wolfe Street, WBSB 708, Baltimore, MD, 21205, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biophysics and Biophysical Chemistry, Johns Hopkins School of Medicine, 725 N. Wolfe Street, WBSB 708, Baltimore, MD, 21205, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029392337"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2790},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2790},"fwci":0.9374,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.71481234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"24","issue":"1","first_page":"84","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.849399983882904,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.849399983882904,"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/T10885","display_name":"Gene expression and cancer classification","score":0.06769999861717224,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.024000000208616257,"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/mutual-information","display_name":"Mutual information","score":0.685509204864502},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6410109996795654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5903193950653076},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4874143898487091},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.46955162286758423},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4622502028942108},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.436714231967926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4237293004989624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41591739654541016},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3728276193141937},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3343391418457031},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2748146951198578},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21417319774627686},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.18011513352394104},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.09455698728561401}],"concepts":[{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.685509204864502},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6410109996795654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5903193950653076},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4874143898487091},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.46955162286758423},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4622502028942108},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.436714231967926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4237293004989624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41591739654541016},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3728276193141937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3343391418457031},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2748146951198578},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21417319774627686},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.18011513352394104},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.09455698728561401},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","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":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D053263","descriptor_name":"Gene Regulatory Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D053263","descriptor_name":"Gene Regulatory Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D053263","descriptor_name":"Gene Regulatory Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12859-022-05047-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-05047-5","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-05047-5","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:36879188","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36879188","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":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9990267","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9990267","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9990267/pdf/12859_2022_Article_5047.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:32530c1f8b214701af58169522c2fd4d","is_oa":true,"landing_page_url":"https://doaj.org/article/32530c1f8b214701af58169522c2fd4d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 24, Iss 1, Pp 1-21 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s12859-022-05047-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-022-05047-5","pdf_url":"https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-022-05047-5","source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G5995319128","display_name":null,"funder_award_id":"MCB1817551","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7201599348","display_name":null,"funder_award_id":"R35 GM124725","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G8114264415","display_name":null,"funder_award_id":"R35GM124725","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310145","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4323310840.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1599969036","https://openalex.org/W1635484243","https://openalex.org/W2018891628","https://openalex.org/W2023348596","https://openalex.org/W2027665171","https://openalex.org/W2044525257","https://openalex.org/W2069986908","https://openalex.org/W2071727203","https://openalex.org/W2078149659","https://openalex.org/W2078450879","https://openalex.org/W2082290707","https://openalex.org/W2092939357","https://openalex.org/W2102456970","https://openalex.org/W2102471334","https://openalex.org/W2106945333","https://openalex.org/W2109384743","https://openalex.org/W2115108153","https://openalex.org/W2122378596","https://openalex.org/W2127234432","https://openalex.org/W2128962304","https://openalex.org/W2135191607","https://openalex.org/W2139997707","https://openalex.org/W2142182986","https://openalex.org/W2143076232","https://openalex.org/W2149620753","https://openalex.org/W2150926065","https://openalex.org/W2161868542","https://openalex.org/W2161922735","https://openalex.org/W2163296115","https://openalex.org/W2169053773","https://openalex.org/W2226988020","https://openalex.org/W2478708596","https://openalex.org/W2757234574","https://openalex.org/W2794402253","https://openalex.org/W2803928488","https://openalex.org/W2850647469","https://openalex.org/W2900007277","https://openalex.org/W2993383518","https://openalex.org/W2997831639","https://openalex.org/W3099289621","https://openalex.org/W3116169118","https://openalex.org/W3127245931","https://openalex.org/W4239403073"],"related_works":["https://openalex.org/W2466816617","https://openalex.org/W1970834875","https://openalex.org/W4287880334","https://openalex.org/W842936808","https://openalex.org/W3174028392","https://openalex.org/W2950199998","https://openalex.org/W2560421304","https://openalex.org/W2951387065","https://openalex.org/W4385727351","https://openalex.org/W4306798985"],"abstract_inverted_index":{"BACKGROUND:":[0],"A":[1],"cell":[2],"exhibits":[3],"a":[4,55,77,149,189,214],"variety":[5,56],"of":[6,23,47,57,97,103,114,148,203,260],"responses":[7,14],"to":[8,20,70,120,168,188,279],"internal":[9],"and":[10,92,125,128,151,254],"external":[11],"cues.":[12],"These":[13],"are":[15],"possible,":[16],"in":[17,30,65,162,192,226,262,270],"part,":[18],"due":[19],"the":[21,35,44,101,181,229,245,255,266,271],"presence":[22],"an":[24,258],"elaborate":[25],"gene":[26,51,115,282,287],"regulatory":[27],"network":[28],"(GRN)":[29],"every":[31],"single":[32],"cell.":[33],"In":[34,139],"past":[36],"20":[37],"years,":[38],"many":[39],"groups":[40],"worked":[41],"on":[42,173],"reconstructing":[43],"topological":[45],"structure":[46],"GRNs":[48,66],"from":[49],"large-scale":[50],"expression":[52,116],"data":[53,107,121],"using":[54,155],"inference":[58,197,216],"algorithms.":[59],"Insights":[60],"gained":[61],"about":[62],"participating":[63],"players":[64],"may":[67],"ultimately":[68],"lead":[69],"therapeutic":[71],"benefits.":[72],"Mutual":[73,220],"information":[74],"(MI)":[75],"is":[76,118],"widely":[78],"used":[79,170,234],"metric":[80],"within":[81],"this":[82,140],"inference/reconstruction":[83],"pipeline":[84],"as":[85,166,200],"it":[86],"can":[87],"detect":[88],"any":[89,95],"correlation":[90,123],"(linear":[91],"non-linear)":[93],"between":[94],"number":[96],"variables":[98],"(n-dimensions).":[99],"However,":[100],"use":[102],"MI":[104,147,159],"with":[105,228],"continuous":[106],"(for":[108],"example,":[109],"normalized":[110],"fluorescence":[111],"intensity":[112],"measurement":[113],"levels)":[117],"sensitive":[119],"size,":[122],"strength":[124],"underlying":[126],"distributions,":[127],"often":[129],"requires":[130],"laborious":[131],"and,":[132],"at":[133],"times,":[134],"ad":[135],"hoc":[136],"optimization.":[137],"RESULTS:":[138],"work,":[141],"we":[142,177,211],"first":[143],"show":[144,212],"that":[145,179,213],"estimating":[146],"bi-":[150],"tri-variate":[152],"Gaussian":[153],"distribution":[154],"k-nearest":[156],"neighbor":[157],"(kNN)":[158],"estimation":[160],"results":[161],"significant":[163,190],"error":[164],"reduction":[165],"compared":[167],"commonly":[169,233],"methods":[171],"based":[172],"fixed":[174],"binning.":[175],"Second,":[176],"demonstrate":[178],"implementing":[180],"MI-based":[182],"kNN":[183],"Kraskov-Sto\u00f6gbauer-Grassberger":[184],"(KSG)":[185],"algorithm":[186,217],"leads":[187],"improvement":[191,259],"GRN":[193,250],"reconstruction":[194],"for":[195,249,289],"popular":[196],"algorithms,":[198],"such":[199],"Context":[201],"Likelihood":[202],"Relatedness":[204],"(CLR).":[205],"Finally,":[206],"through":[207],"extensive":[208],"in-silico":[209],"benchmarking":[210],"new":[215,274,281],"CMIA":[218],"(Conditional":[219],"Information":[221],"Augmentation),":[222],"inspired":[223],"by":[224],"CLR,":[225],"combination":[227],"KSG-MI":[230,256],"estimator,":[231],"outperforms":[232],"methods.":[235],"CONCLUSIONS:":[236],"Using":[237],"three":[238],"canonical":[239],"datasets":[240],"containing":[241],"15":[242],"synthetic":[243],"networks,":[244],"newly":[246],"developed":[247],"method":[248,275],"reconstruction-which":[251],"combines":[252],"CMIA,":[253],"estimator-achieves":[257],"20-35%":[261],"precision-recall":[263],"measures":[264],"over":[265],"current":[267],"gold":[268],"standard":[269],"field.":[272],"This":[273],"will":[276],"enable":[277],"researchers":[278],"discover":[280],"interactions":[283],"or":[284],"better":[285],"choose":[286],"candidates":[288],"experimental":[290],"validations.":[291]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}