{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T05:28:18Z","timestamp":1771997298203,"version":"3.50.1"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82060329"],"award-info":[{"award-number":["82060329"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11265007"],"award-info":[{"award-number":["11265007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81860318"],"award-info":[{"award-number":["81860318"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific Research Fund Project of Yunnan Education Department of China","award":["2020J0052"],"award-info":[{"award-number":["2020J0052"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Microbiome is closely related to many major human diseases, but it is generally analyzed by the traditional statistical methods such as principal component analysis, principal coordinate analysis, etc. These methods have shortcomings and do not consider the characteristics of the microbiome data itself (i.e., the \u201cprobability distribution\u201d of microbiome).\u00a0A new method based on probabilistic topic model was proposed to mine the information of gut microbiome in this paper, taking gut microbiome of type 2 diabetes patients and healthy subjects as an example. Firstly, different weights were assigned to different microbiome according to the degree of correlation between different microbiome and subjects. Then a probabilistic topic model was employed to obtain the probabilistic distribution of gut microbiome (i.e., per-topic OTU (operational taxonomic units, OTU) distribution and per-patient topic distribution).\u00a0Experimental results showed that the output topics can be used as the characteristics of gut microbiome, and can describe the differences of gut microbiome over different groups. Furthermore, in order to verify the ability of this method to characterize gut microbiome, clustering and classification operations on the distributions over topics for gut microbiome in each subject were performed, and the experimental results showed that the clustering and classification performance has been improved, and the recognition rate of three groups reached 100%.\u00a0The proposed method could mine the information hidden in gut microbiome data, and the output topics could describe the characteristics of gut microbiome, which provides a new perspective for the study of gut microbiome.<\/jats:p>","DOI":"10.1007\/s11042-022-13916-7","type":"journal-article","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T13:04:18Z","timestamp":1665666258000},"page":"16081-16104","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A new method for mining information of gut microbiome with probabilistic topic models"],"prefix":"10.1007","volume":"82","author":[{"given":"Xin","family":"Xiong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minrui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuyan","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xusheng","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhui","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingsong","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangyang","family":"Kong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianfeng","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,13]]},"reference":[{"issue":"Suppl 2","key":"13916_CR1","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1186\/s12864-019-5476-9","volume":"20","author":"K Abe","year":"2019","unstructured":"Abe K, Hirayama M, Ohno K, Shimamura T (2019) ENIGMA: an enterotype-like unigram mixture model for microbial association analysis. BMC Genom 20(Suppl 2):191","journal-title":"BMC Genom"},{"issue":"7346","key":"13916_CR2","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1038\/nature09944","volume":"473","author":"M Arumugam","year":"2011","unstructured":"Arumugam M, Raes J (2011) Eric Pelletier. Enterotypes of the human gut microbiome. Nature 473(7346):174\u2013180","journal-title":"Nature"},{"issue":"3","key":"13916_CR3","first-page":"1","volume":"59","author":"F Azpiroz","year":"2015","unstructured":"Azpiroz F, Malagelada C (2015) Diabetic neuropathy in the gut: pathogenesis and diagnosis[J]. Diabetologia 59(3):1\u20135","journal-title":"Diabetologia"},{"issue":"15","key":"13916_CR4","doi-asserted-by":"publisher","first-page":"S6","DOI":"10.1186\/1471-2105-13-S15-S6","volume":"13","author":"H Bisgin","year":"2012","unstructured":"Bisgin H, Liu Z, Kelly R, Fang H, Xu X, Tong W (2012) Investigating drug repositioning opportunities in FDA drug labels through topic modeling. BMC Bioinformatics 13(15):S6","journal-title":"BMC Bioinformatics"},{"key":"13916_CR5","doi-asserted-by":"crossref","unstructured":"Blei D, Jordan M (2003) Modeling annotated data. The Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval, pp 127\u2013134","DOI":"10.1145\/860435.860460"},{"key":"13916_CR6","unstructured":"Blei D, Ng A, Jordan M (2003) Latent dirichlet allocation. J Mach Learn Res 3:993\u20131022"},{"issue":"1","key":"13916_CR7","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45(1):5\u201332","journal-title":"Mach Learn"},{"key":"13916_CR8","doi-asserted-by":"publisher","first-page":"3698","DOI":"10.2337\/dc13-0347","volume":"36","author":"C Brock","year":"2013","unstructured":"Brock C (2013) Diabetic autonomic neuropathy affects symptom generation and brain-gut axis. Diabetes Care 36:3698\u20133705","journal-title":"Diabetes Care"},{"key":"13916_CR9","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/0302-3524(76)90041-4","volume":"4","author":"P Chardy","year":"1974","unstructured":"Chardy P, Glemarec M, Laurec A (1974) Application of inertia methods of benthic marine ecology: Practical implications of the basic options. Estuar Coast Mar Sci 4:179\u2013205","journal-title":"Estuar Coast Mar Sci"},{"key":"13916_CR10","doi-asserted-by":"crossref","unstructured":"Chen X, He T, Hu X (2012) Estimating functional groups in human gut microbiome with probabilistic topic models. IEEE Trans Nanobiosci 11(3):203\u2013215","DOI":"10.1109\/TNB.2012.2212204"},{"issue":"2","key":"13916_CR11","doi-asserted-by":"publisher","first-page":"e4600","DOI":"10.7717\/peerj.4600","volume":"6","author":"L Chen","year":"2018","unstructured":"Chen L, Reeve J, Zhang L (2018) GMPR: a robust normalization method for zero-inflated count data with application to microbiome sequencing data. PeerJ 6(2):e4600","journal-title":"PeerJ"},{"issue":"6086","key":"13916_CR12","doi-asserted-by":"publisher","first-page":"1255","DOI":"10.1126\/science.1224203","volume":"336","author":"E Costello","year":"2012","unstructured":"Costello E, Stagaman K, Dethlefsen L (2012) The application of ecological theory toward an understanding of the human microbiome. Science 336(6086):1255\u20131262","journal-title":"Science"},{"key":"13916_CR13","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1038\/nature12480","volume":"500","author":"A Cotillard","year":"2013","unstructured":"Cotillard A, Kennedy S, Kong L (2013) Dietary intervention impact on gut microbial gene richness. Nature 500:585\u2013588","journal-title":"Nature"},{"issue":"2","key":"13916_CR14","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1145\/1348246.1348248","volume":"40","author":"R Datta","year":"2008","unstructured":"Datta R, Joshi D, Li J, Wang J (2008) Image retrieval: ideas, influences, and trends of the new age. ACM Comput Surv 40(2):5","journal-title":"ACM Comput Surv"},{"issue":"1","key":"13916_CR15","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1186\/s12859-016-1175-6","volume":"17","author":"A Duverle","year":"2016","unstructured":"Duverle A, Yotsukura S, Nomura S (2016) CellTree: an R\/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data. BMC Bioinformatics 17(1):363","journal-title":"BMC Bioinformatics"},{"issue":"12","key":"13916_CR16","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1016\/j.disamonth.2005.11.002","volume":"51","author":"EC Ebert","year":"2005","unstructured":"Ebert EC (2005) Gastrointestinal complications of diabetes mellitus. Dis Mon 51(12):620\u2013663","journal-title":"Dis Mon"},{"issue":"5879","key":"13916_CR17","doi-asserted-by":"publisher","first-page":"1034","DOI":"10.1126\/science.1153213","volume":"320","author":"P Falkowski","year":"2008","unstructured":"Falkowski P, Fenchel T, Delong E (2008) The microbial engines that drive Earth\u2019s biogeochemical cycles. Science 320(5879):1034\u20131039","journal-title":"Science"},{"issue":"5","key":"13916_CR18","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1007\/s11894-009-0054-y","volume":"11","author":"M Gould","year":"2009","unstructured":"Gould M, Sellin JH (2009) Diabetic diarrhea[J]. Curr Gastroenterol Rep 11(5):354\u2013359","journal-title":"Curr Gastroenterol Rep"},{"issue":"suppl. 1","key":"13916_CR19","doi-asserted-by":"publisher","first-page":"5228","DOI":"10.1073\/pnas.0307752101","volume":"101","author":"T Griffiths","year":"2004","unstructured":"Griffiths T, Steyvers M (2004) Finding scientific topics. Proc Natl Acad Sci USA 101(suppl. 1):5228\u20135235","journal-title":"Proc Natl Acad Sci USA"},{"issue":"SEP.","key":"13916_CR20","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.ijar.2019.05.010","volume":"112","author":"C Ha","year":"2019","unstructured":"Ha C, Iran D, Van N, Than K (2019) Eliminating overfitting of probabilistic topic models on short and noisy text: the role of dropou. Int J Approx Reason 112(SEP.):85\u2013104","journal-title":"Int J Approx Reason"},{"issue":"4","key":"13916_CR21","first-page":"539","volume":"11","author":"J Hao","year":"2016","unstructured":"Hao J, Xie J, Su J, Xu X, Han X (2016) An unsupervised approach for sentiment classification based on weighted latent dirichlet allocation. CAAI Trans Intell Syst 11(4):539\u2013545","journal-title":"CAAI Trans Intell Syst"},{"key":"13916_CR22","doi-asserted-by":"crossref","unstructured":"Hofmann T (1999) Probabilistic latent semantic indexing. Annual international ACM SIGIR conference on Research and development in information retrieval, pp 50\u201357","DOI":"10.1145\/312624.312649"},{"key":"13916_CR23","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1023\/A:1007617005950","volume":"42","author":"T Hofmann","year":"2001","unstructured":"Hofmann T (2001) Unsupervised learning by probabilistic latent semantic analysis. Mach Learn 42:177\u2013196","journal-title":"Mach Learn"},{"key":"13916_CR24","unstructured":"Hoffman M, Blei D, Bach F (2010) Online learning for latent dirichlet allocation. In: Lafferty J, Williams CKI, Shawe-Taylor J, Zemel R, Culotta A (Eds) Advances in neural information processing systems, 23, pp 856\u2013864"},{"issue":"2","key":"13916_CR25","doi-asserted-by":"publisher","first-page":"e30126","DOI":"10.1371\/journal.pone.0030126","volume":"7","author":"I Holmes","year":"2012","unstructured":"Holmes I, Harris K, Quince C (2012) Dirichlet multinomial mixtures: generative models for microbial metagenomics. PLoS One 7(2):e30126","journal-title":"PLoS One"},{"key":"13916_CR26","doi-asserted-by":"crossref","unstructured":"Hubert L, Arabie P (1985) Comparing partitions. J Classif 2(2\u20133):193\u2013218","DOI":"10.1007\/BF01908075"},{"issue":"6068","key":"13916_CR27","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1126\/science.1212665","volume":"335","author":"V Iverson","year":"2012","unstructured":"Iverson V, Morris R, Frazar C (2012) Untangling genomes from metagenomes: revealing an uncultured class of marine euryarchaeota. Science 335(6068):587\u2013590","journal-title":"Science"},{"issue":"3","key":"13916_CR28","first-page":"6","volume":"4","author":"X Jiang","year":"2015","unstructured":"Jiang X, Hu X (2015) Big data research in microbiome. Math Model Appl\u00a0 4(3):6\u201318","journal-title":"Math Model Appl\u00a0"},{"key":"13916_CR29","doi-asserted-by":"crossref","unstructured":"Jordan M (1999) Learning in graphical models. MIT Press, Cambridge","DOI":"10.1007\/978-94-011-5014-9"},{"issue":"7452","key":"13916_CR30","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1038\/nature12198","volume":"498","author":"F Karlsson","year":"2013","unstructured":"Karlsson F, Tremaroli V, Nookaew I (2013) Gut metagenome in European women with normal, impaired and diabetic glucose control. Nature 498(7452):99\u2013103","journal-title":"Nature"},{"key":"13916_CR31","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.image.2019.05.012","volume":"76","author":"L Laib","year":"2019","unstructured":"Laib L, Allili S, Ait-Aoudia S (2019) A probabilistic topic model for event-based image classification and multi-label annotation. Sig Process Image Commun 76:283\u2013294","journal-title":"Sig Process Image Commun"},{"key":"13916_CR32","doi-asserted-by":"crossref","unstructured":"Lambeth S, Carson T, Lowe J (2015) Composition, diversity and abundance of gut microbiome in prediabetes and type 2 diabetes. J Diabetes Obes 2(3):1\u20137","DOI":"10.15436\/2376-0949.15.031"},{"issue":"2","key":"13916_CR33","doi-asserted-by":"publisher","first-page":"e9085","DOI":"10.1371\/journal.pone.0009085","volume":"5","author":"N Larsen","year":"2010","unstructured":"Larsen N, Vogensen F, van den Berg F (2010) Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS ONE 5(2):e9085","journal-title":"PLoS ONE"},{"key":"13916_CR34","unstructured":"Li X, Wang Y, Li Z et al. (2015) The Correlation between intestinal flora and diabetes: research progress. Chin J Microecol 27(10):1224\u20131228"},{"key":"13916_CR35","doi-asserted-by":"crossref","unstructured":"Okui T (2020) A Bayesian nonparametric topic model for microbiome data using subject attributes. IPSJ Trans Bioinf 13:1\u20136","DOI":"10.2197\/ipsjtbio.13.1"},{"key":"13916_CR36","doi-asserted-by":"crossref","unstructured":"Papadimitriou C, Tamaki H, Raghavan P, Vempala S (1998) Latent semantic indexing: a probabilistic analysis. ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems, pp 159\u2013168","DOI":"10.1145\/275487.275505"},{"key":"13916_CR37","doi-asserted-by":"crossref","unstructured":"Phan X, Nguyen L, Horiguchi S (2008) Learning to classify short and sparse text & web with hidden topics from large-scale data collections. Proceedings of the 17th international conference on world wide web. ACM","DOI":"10.1145\/1367497.1367510"},{"issue":"7418","key":"13916_CR38","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1038\/nature11450","volume":"490","author":"J Qin","year":"2012","unstructured":"Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F, Liang S, Zhang W (2012) A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490(7418):55\u201360","journal-title":"Nature"},{"issue":"12","key":"13916_CR39","doi-asserted-by":"publisher","first-page":"e0145499","DOI":"10.1371\/journal.pone.0145499","volume":"10","author":"D Rajpal","year":"2015","unstructured":"Rajpal D, Klein J, Mayhew D (2015) Selective spectrum antibiotic modulation of the gut microbiome in obesity and diabetes rodent models. PLoS ONE 10(12):e0145499","journal-title":"PLoS ONE"},{"issue":"2","key":"13916_CR40","doi-asserted-by":"publisher","first-page":"371","DOI":"10.2337\/diacare.24.2.371","volume":"24","author":"CK Rayner","year":"2001","unstructured":"Rayner CK et al (2001) Relationships of upper gastrointestinal motor and sensory function with glycemic control. Diabetes Care 24(2):371\u2013381","journal-title":"Diabetes Care"},{"issue":"8","key":"13916_CR41","doi-asserted-by":"publisher","first-page":"2343","DOI":"10.2337\/dc13-2817","volume":"37","author":"J Sato","year":"2014","unstructured":"Sato J, Kanazawa A, Ikeda F (2014) Gut dysbiosis and detection of \u201clive gut bacteria\u201d in blood of Japanese patients with type 2 diabetes. Diabetes Care 37(8):2343\u20132350","journal-title":"Diabetes Care"},{"issue":"17","key":"13916_CR42","doi-asserted-by":"publisher","first-page":"4159","DOI":"10.1113\/jphysiol.2009.172742","volume":"587","author":"I Sekirov","year":"2009","unstructured":"Sekirov I, Finlay B (2009) The role of the intestinal microbiota in enteric infection. J Physiol 587(17):4159\u20134167","journal-title":"J Physiol"},{"issue":"13","key":"13916_CR43","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1093\/bioinformatics\/btr249","volume":"27","author":"S Shivashankar","year":"2011","unstructured":"Shivashankar S, Srivathsan S, Ravindran B, Tendulkar A (2011) Multi-view methods for protein structure comparison using latent dirichlet allocation. Bioinformatics 27(13):161\u2013168","journal-title":"Bioinformatics"},{"key":"13916_CR44","unstructured":"Taddy M (2012) On estimation and selection for topic models. In: AISTATS, pp 1184\u20131193"},{"issue":"2","key":"13916_CR45","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1007\/s13042-019-00983-w","volume":"11","author":"D Tian","year":"2020","unstructured":"Tian D, Shi Z (2020) A two-stage hybrid probabilistic topic model for refining image annotation. Int J Mach Learn Cybernet 11(2):417\u2013431","journal-title":"Int J Mach Learn Cybernet"},{"issue":"7415","key":"13916_CR46","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1038\/nature11552","volume":"489","author":"V Tremaroli","year":"2012","unstructured":"Tremaroli V, Backhed F (2012) Functional interactions between the gut microbiota and host metabolism. Nature 489(7415):242\u2013249","journal-title":"Nature"},{"issue":"4","key":"13916_CR47","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1145\/944012.944013","volume":"21","author":"D Turney","year":"2003","unstructured":"Turney D, Littman L (2003) Measuring praise and criticism: inference of semantic orientation from association. ACM Trans Inform Syst 21(4):315\u2013346","journal-title":"ACM Trans Inform Syst"},{"key":"13916_CR48","doi-asserted-by":"crossref","unstructured":"Vapnik V (1995) The nature of statistical learning theory. Springer, New York","DOI":"10.1007\/978-1-4757-2440-0"},{"issue":"7728","key":"13916_CR49","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1038\/s41586-018-0620-2","volume":"562","author":"T Vatanen","year":"2018","unstructured":"Vatanen T, Franzosa E, Schwager R (2018) The human gut microbiome in early-onset type 1diabetes from the TEDDY study. Nature 562(7728):589\u2013594","journal-title":"Nature"},{"issue":"6","key":"13916_CR50","first-page":"530","volume":"24","author":"M Virally-Monod","year":"1999","unstructured":"Virally-Monod M, Tielmans D, Kevorkian JP et al (1999) Chronic diarrhoea and diabetes mellitus: prevalence of small intestinal bacterial overgrowth[J]. Diabet Metab 24(6):530\u2013536","journal-title":"Diabet Metab"},{"issue":"5815","key":"13916_CR51","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1126\/science.1133420","volume":"315","author":"C von Mering","year":"2007","unstructured":"von Mering C, Hugenholtz P, Raes J (2007) Quantitative phylogenetic assessment of microbial communities in diverse environments. Science 315(5815):1126\u20131130","journal-title":"Science"},{"key":"13916_CR52","doi-asserted-by":"crossref","unstructured":"Wallach H (2006) Topic modeling: beyond bag-of-words. International conference on machine learning. ACM","DOI":"10.1145\/1143844.1143967"},{"key":"13916_CR53","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.1360\/N052017-00105","volume":"47","author":"X Wang","year":"2017","unstructured":"Wang X, Zuo Z, Zhou L (2017) Microbial flora structure based on probability topic model. Sci Sin Vitae 47:1220\u20131234","journal-title":"Sci Sin Vitae"},{"key":"13916_CR54","unstructured":"Wang X, Zuo Z, Fan H (2018) Study of the structure of intestinal microflora in patients with mild hepatic encephalopathy based on probability topic model. Acta Microbiol Sinica 58(7):1274\u20131286"},{"key":"13916_CR55","doi-asserted-by":"crossref","unstructured":"Wei X, Croft W (2006) LDA-based document models for Ad-hoc retrieval. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, pp 178\u2013185","DOI":"10.1145\/1148170.1148204"},{"key":"13916_CR56","doi-asserted-by":"crossref","unstructured":"Woloszynek S, Zhao Z, Simpson G, O\u2019Connor P, Mell G (2017) Evaluating a topic model approach for parsing microbiome data structure. bioRxiv, pp 176412\u201317636","DOI":"10.1101\/176412"},{"issue":"6052","key":"13916_CR57","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1126\/science.1208344","volume":"334","author":"G Wu","year":"2011","unstructured":"Wu G, Chen J, Hoffmann C (2011) Linking Long-Term Dietary Patterns with Gut Microbial Enterotypes. Science 334(6052):105\u2013108","journal-title":"Science"},{"issue":"5","key":"13916_CR58","doi-asserted-by":"publisher","first-page":"S2","DOI":"10.1186\/1471-2105-16-S5-S2","volume":"16","author":"R Zhang","year":"2015","unstructured":"Zhang R, Cheng Z, Guan J, Zhou S (2015) Exploiting topic modeling to boost metagenomic reads binning. BMC Bioinformatics 16(5):S2","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"13916_CR59","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1186\/s12859-016-1156-9","volume":"17","author":"W Zhao","year":"2016","unstructured":"Zhao W, Chen J, Perkins R (2016) A novel procedure on next generation sequencing data analysis using text mining algorithm. BMC Bioinformatics 17(1):301","journal-title":"BMC Bioinformatics"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13916-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13916-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13916-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,15]],"date-time":"2023-04-15T09:19:01Z","timestamp":1681550341000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13916-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,13]]},"references-count":59,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["13916"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13916-7","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,13]]},"assertion":[{"value":"28 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 March 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 September 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The experiment was approved by the ethics committee of Kunming University of science and technology.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}