Acta Laser Biology Sinica, Volume. 31, Issue 5, 440(2022)
Improved Clustering Algorithm Based on Spectrum for Gut Microbiome
[1] [1] YI B, HUANG G, ZHOU Z. Different role of zinc transporter 8 between type 1 diabetes mellitus and type 2 diabetes mellitus[J]. Journal of Diabetes Investigation, 2016, 7(4): 459-465.
[6] [6] ORTIZ M, JACAS C, CORDOBA J. Minimal hepatic encephalopathy: diagnosis, clinical significance and recommendations[J]. Journal of Hepatology, 2005, 42(Supplement): S45-S53.
[7] [7] ALLAMPATI S, DUARTE-ROJO A, THACKE L R, et al. Diagnosis of minimal hepatic encephalopathy using stroop encephalapp: a multicenter US-based, norm-based study[J]. American Journal of Gastroenterology, 2016, 111(1): 78-86.
[8] [8] QIN J, LI Y, CAI Z, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes[J]. Nature, 2012, 490(7418): 55-60.
[9] [9] LAMBETH S M, CARSON T, LOWE J, et al. Composition, diversity and abundance of gut microbiome in prediabetes and type 2 diabetes[J]. Journal of Diabetes and Obesity, 2015, 2(3): 1-7.
[10] [10] LARSEN N, VOGESEN F K, VAN DEN BERG F W, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults[J]. PLoS One, 2010, 5(2): e9085.
[11] [11] RAJPAL D K, KLEIN J L, MAYHEW D, et al. Selective spectrum antibiotic modulation of the gut microbiome in obesity and diabetes rodent models[J]. PLoS One, 2015, 10(12): e0145499.
[12] [12] STEWART C J, AJAMI N J, O’BRIEN J L, et al. Temporal development of the gut microbiome in early childhood from the TEDDY study[J]. Nature, 2018, 562(7728): 583-588.
[13] [13] VATANEN T, FRANZOSA E A, SCHWAGER R, et al. The human gut microbiome in early-onset type 1 diabetes from the TEDDY study[J]. Nature, 2018, 562(7728): 589-594.
[14] [14] ARUMUGAM M, RAES J, PELLETIER E, et al. Enterotypes of the human gut microbiome[J]. Nature, 2011, 473(7346): 174-180.
[15] [15] WU G D, CHEN J, HOFFMANN C, et al. Linking long-term dietary patterns with gut microbial enterotypes[J]. Science, 2011, 334(6052): 105-108.
[16] [16] MACQUEEN J. Some methods for classification and analysis of multivariate observations[C]//Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1967, 1(14): 281-297.
[17] [17] GUHA S, RASTOGI R, SHIM K. CURE: an efficient clustering algorithm for large databases[J]. ACM Sigmod Record, 1998, 27(2): 73-84.
[18] [18] ZHANG T, RAMAKRISHNAN R, LIVNY M. BIRCH: an efficient data clustering method for very large databases[J]. ACM Sigmod Record, 1996, 25(2): 103-114.
[19] [19] AGRAWAL R, GEHRKE J, GUNOPULOS D, et al. Automatic subspace clustering of high dimensional data for data mining applications[C]//Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, 1998: 94-105.
[20] [20] WANG W, YANG J, MUNTZ R. STING: a statistical information grid approach to spatial data mining[C]//Vldb, 1997, 97: 186-195.
[22] [22] ZELNIK-MANOR L, PERONA P. Self-tuning spectral clustering[C]//In Proceedings of the 17th International Conference on Neural Information Processing Systems (NIPS). 2004: 1601-1608.
[24] [24] XIE J, ZHOU Y, DING L. Local standard deviation spectral clustering[C]//2018 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE Computer Society, 2018: 242-250.
[25] [25] CHEN L, REEVE J, ZHANG L, et al. GMPR: a robust normalization method for zero-inflated count data with application to microbiome sequencing data[J]. PeerJ, 2018, 6: e4600.
[26] [26] JOHN C R, WATSON D, BARNES M R, et al. Spectrum: fast density-aware spectral clustering for single and multi-omic data[J]. Bioinformatics, 2020, 36(4): 1159-1166.
[27] [27] SAADE A, KRZAKALA F, ZDEBOROVA L. Spectral density of the non-backtracking operator on random graphs[J]. Europhysics Letters, 2014, 107(5): 50005.
[28] [28] KRZAKALA F, MOORE C, MOSSEL E, et al. Spectral redemption in clustering sparse networks[J]. Proceedings of the National Academy of Sciences, 2013, 110(52): 20935-20940.
[31] [31] SAADE A, KRZAKALA F, ZDEBOROVA L. Spectral clustering of graphs with the Bethe Hessian[J]. Advances in Neural Information Processing Systems, 2014, 27: 1-9.
[32] [32] ROGERS T, CASTILLOI P, KüHN R, et al. Cavity approach to the spectral density of sparse symmetric random matrices[J]. Physical Review E Statal Nonlinear & Soft Matter Physics, 2008, 78(3 Pt 1): 031116.
[33] [33] GUARNER F, MALAGELADA J R. Gut flora in health and disease[J]. Lancet, 2003, 361(9356): 512-519.
[34] [34] CAPORASO J G, LAUBER C L, WALTERS W A, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample[J]. Proceedings of the National Academy of Sciences of the United States of America, 2011, 108: 4516-4522.
[36] [36] HUBERT L, ARABIE P. Comparing partitions[J]. Journal of Classification, 1985, 2(1): 193-218.
[37] [37] REMELY M, DWORZAK S, HIPPE B, et al. Abundance and diversity of microbiota in type 2 diabetes and obesity[J]. Diabetes Metab, 2013, 4(3): 100253.
[38] [38] LARSEN N, VOGENSEN F K, VAN DEN BERG F W J, et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults[J]. PLoS One, 2010, 5(2): e9085.
[39] [39] MURRI M, LEIVA I, GOMEZ-ZUMAQUERO J M, et al. Gut microbiota in children with type 1 diabetes differs from that in healthy children: a case-control study[J]. BMC Medicine, 2013, 11(1): 1-12.
[40] [40] EGSHATYAN L, KASHTANOVA D, POPENKO A, et al. Gut microbiota and diet in patients with various glucose tolerance[J]. Endocrine Abstracts, 2016, 5(1): 1-9.
Get Citation
Copy Citation Text
REN Yuyan, XIONG Xin, HE Jianfeng. Improved Clustering Algorithm Based on Spectrum for Gut Microbiome[J]. Acta Laser Biology Sinica, 2022, 31(5): 440
Category:
Received: Apr. 22, 2022
Accepted: --
Published Online: Jan. 18, 2023
The Author Email: Jianfeng HE (jfenghe@qq.com)