{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T01:51:52Z","timestamp":1775872312433,"version":"3.50.1"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"20","license":[{"start":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:00:00Z","timestamp":1620691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72071206"],"award-info":[{"award-number":["72071206"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Innovation Program of Hunan Province","award":["2020RC4046"],"award-info":[{"award-number":["2020RC4046"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Modeling microbiome systems as complex networks are known as the problem of network inference. Microbial association network inference is of great significance in applications on clinical diagnosis, disease treatment, pathological analysis, etc. However, most current network inference methods focus on mining strong pairwise associations between microorganisms, which is defective in reflecting the comprehensive interactive patterns participated by multiple microorganisms. It is also possible that the microorganisms involved in the generated network are not dominant in the microbiome due to the mere focus on the strength of pairwise associations. Some scholars tried to mine comprehensive microbial associations by association rule mining methods, but the adopted algorithms are relatively basic and have severe limitations such as low calculation efficiency, lacking the ability of mining negative correlations and high redundancy in results, making it difficult to mine high-quality microbial association rules and accurately infer microbial association networks.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We proposed a microbial association network inference method \u2018MANIEA\u2019 based on the improved Eclat algorithm for mining positive and negative microbial association rules. We also proposed a new method for transforming association rules into microbial association networks, which can effectively demonstrate the co-occurrence and causal correlations in association rules. An experiment was conducted on three authentic microbial abundance datasets to compare the \u2018MANIEA\u2019 with currently popular network inference methods, which demonstrated that the proposed \u2018MANIEA\u2019 show advantages in aspects of correlation forms, computation efficiency, adjustability and network characteristics.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The algorithms and data are available at: https:\/\/github.com\/MaidiL\/MANIEA.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab241","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T15:56:11Z","timestamp":1618242971000},"page":"3569-3578","source":"Crossref","is-referenced-by-count":11,"title":["MANIEA: a microbial association network inference method based on improved Eclat association rule mining algorithm"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7914-0772","authenticated-orcid":false,"given":"Maidi","family":"Liu","sequence":"first","affiliation":[{"name":"College of Systems Engineering, National University of Defense Technology , 410073 Changsha, China"}]},{"given":"Yanqing","family":"Ye","sequence":"additional","affiliation":[{"name":"College of Systems Engineering, National University of Defense Technology , 410073 Changsha, China"}]},{"given":"Jiang","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Systems Engineering, National University of Defense Technology , 410073 Changsha, China"}]},{"given":"Kewei","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Systems Engineering, National University of Defense Technology , 410073 Changsha, China"}]}],"member":"286","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"2023051608571839600_btab241-B1","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-30116-5_6","article-title":"Mining positive and negative association rules: an approach for confined rules","author":"Antonie","year":"2004"},{"key":"2023051608571839600_btab241-B2","doi-asserted-by":"crossref","first-page":"3617","DOI":"10.1093\/bioinformatics\/btv414","article-title":"A Bayesian approach for structure learning in oscillating regulatory networks","volume":"31","author":"Banos","year":"2015","journal-title":"Bioinformatics"},{"key":"2023051608571839600_btab241-B3","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1186\/s13073-016-0290-3","article-title":"Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions","volume":"8","author":"Baxter","year":"2016","journal-title":"Genome Med"},{"key":"2023051608571839600_btab241-B6","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1186\/1471-2105-13-113","article-title":"Molecular ecological network analyses","volume":"13","author":"Deng","year":"2012","journal-title":"BMC Bioinform"},{"key":"2023051608571839600_btab241-B7","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1038\/nrmicro2419","article-title":"Advantages and limitations of current network inference methods","volume":"8","author":"De Smet","year":"2010","journal-title":"Nat. Rev. Microbiol"},{"key":"2023051608571839600_btab241-B8","doi-asserted-by":"crossref","first-page":"1784","DOI":"10.1038\/s41467-017-01973-8","article-title":"Meta-analysis of gut microbiome studies identifies disease-specific and shared responses","volume":"8","author":"Duvallet","year":"2017","journal-title":"Nat. Commun"},{"key":"2023051608571839600_btab241-B9","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1038\/nrmicro2832","article-title":"Microbial interactions: from networks to models","volume":"10","author":"Faust","year":"2012","journal-title":"Nat. Rev. Microbiol"},{"key":"2023051608571839600_btab241-B10","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1002\/spe.4380211102","article-title":"Graph drawing by force-directed placement","volume":"21","author":"Fruchterman","year":"1991","journal-title":"Softw. Pract. Exp"},{"key":"2023051608571839600_btab241-B12","first-page":"1","article-title":"Going viral: a novel role for bacteriophage in colo-rectal cancer","volume":"10","author":"Handley","year":"2019","journal-title":"Am. Soc. Microbiol"},{"key":"2023051608571839600_btab241-B13","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1158\/2159-8290.CD-13-0042","article-title":"Colorectal cancer: looking for answers in the microbiota","volume":"3","author":"Jobin","year":"2013","journal-title":"Cancer Disc"},{"key":"2023051608571839600_btab241-B14","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/0020-0190(89)90102-6","article-title":"An algorithm for drawing general undirected graphs","volume":"31","author":"Kamada","year":"1989","journal-title":"Inf. Process. Lett"},{"key":"2023051608571839600_btab241-B15","first-page":", 2011","article-title":"Construction and analysis of co-occurrence network in the gut microbiome","volume":"58","author":"Ma","year":"2018","journal-title":"Acta Microbiol. Sin"},{"key":"2023051608571839600_btab241-B16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2013.09.009","article-title":"QAR-CIP-NSGA-II: a new multi-objective evolutionary algorithm to mine quantitative association rules","volume":"258","author":"Martin","year":"2014","journal-title":"Inf. Sci"},{"key":"2023051608571839600_btab241-B17","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1093\/gbe\/evu050","article-title":"A phylogenomic view of ecological specialization in the lachnospiraceae, a family of digestive tract-associated bacteria","volume":"6","author":"Meehan","year":"2014","journal-title":"Genome Biol. Evol"},{"key":"2023051608571839600_btab241-B19","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1186\/s40168-015-0109-2","article-title":"Intestinal microbial communities associated with acute enteric infections and disease recovery","volume":"3","author":"Singh","year":"2015","journal-title":"Microbiome"},{"key":"2023051608571839600_btab241-B20","doi-asserted-by":"crossref","first-page":"e0154493","DOI":"10.1371\/journal.pone.0154493","article-title":"Inferring intra-community microbial interaction patterns from metagenomic datasets using associative rule mining techniques","volume":"11","author":"Tandon","year":"2016","journal-title":"PLoS One"},{"key":"2023051608571839600_btab241-B21","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1039\/B916989J","article-title":"Network inference and network response identification: moving genome-scale data to the next level of biological discovery","volume":"6","author":"Veiga","year":"2010","journal-title":"Mol. Biosyst"},{"key":"2023051608571839600_btab241-B22","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511815478","volume-title":"Social Network Analysis: Methods and Applications","author":"Wasserman","year":"1994"},{"key":"2023051608571839600_btab241-B23","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of \u2018small-world\u2019 networks","volume":"393","author":"Watts","year":"1998","journal-title":"Nature"},{"key":"2023051608571839600_btab241-B24","volume-title":"Introduction to Graph Theory","author":"West","year":"1996"},{"key":"2023051608571839600_btab241-B25","first-page":"108","article-title":"An improved CLOSET algorithm","volume":"16","author":"Wu","year":"2008","journal-title":"Chin. J. Manage. Sci"},{"key":"2023051608571839600_btab241-B26","doi-asserted-by":"crossref","DOI":"10.1145\/956750.956788","article-title":"Fast vertical mining using diffsets","author":"Zaki","year":"2003"},{"key":"2023051608571839600_btab241-B27","doi-asserted-by":"crossref","first-page":"e43052","DOI":"10.1371\/journal.pone.0043052","article-title":"Analysis of the gut microbiota in the old order Amish and its relation to the metabolic syndrome","volume":"7","author":"Zupancic","year":"2012","journal-title":"PLoS One"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btab241\/39590358\/btab241.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/20\/3569\/50338388\/btab241.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/20\/3569\/50338388\/btab241.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T08:57:59Z","timestamp":1684227479000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/37\/20\/3569\/6273657"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,5,11]]},"references-count":23,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2021,10,25]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btab241","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2021,10,15]]},"published":{"date-parts":[[2021,5,11]]}}}