BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Hirano H, Takemoto K. Difficulty in inferring microbial community structure based on co-occurrence network approaches. BMC Bioinformatics 2019;20:329. [PMID: 31195956 DOI: 10.1186/s12859-019-2915-1] [Cited by in Crossref: 36] [Cited by in F6Publishing: 24] [Article Influence: 12.0] [Reference Citation Analysis]
Number Citing Articles
1 Matchado MS, Lauber M, Reitmeier S, Kacprowski T, Baumbach J, Haller D, List M. Network analysis methods for studying microbial communities: A mini review. Comput Struct Biotechnol J 2021;19:2687-98. [PMID: 34093985 DOI: 10.1016/j.csbj.2021.05.001] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
2 Vázquez-castellanos JF, Biclot A, Vrancken G, Huys GR, Raes J. Design of synthetic microbial consortia for gut microbiota modulation. Current Opinion in Pharmacology 2019;49:52-9. [DOI: 10.1016/j.coph.2019.07.005] [Cited by in Crossref: 13] [Cited by in F6Publishing: 12] [Article Influence: 4.3] [Reference Citation Analysis]
3 Coenen AR, Hu SK, Luo E, Muratore D, Weitz JS. A Primer for Microbiome Time-Series Analysis. Front Genet 2020;11:310. [PMID: 32373155 DOI: 10.3389/fgene.2020.00310] [Cited by in Crossref: 11] [Cited by in F6Publishing: 5] [Article Influence: 5.5] [Reference Citation Analysis]
4 Grossart H, Massana R, Mcmahon KD, Walsh DA. Linking metagenomics to aquatic microbial ecology and biogeochemical cycles. Limnol Oceanogr 2020;65. [DOI: 10.1002/lno.11382] [Cited by in Crossref: 21] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
5 Dopheide A, Davis C, Nuñez J, Rogers G, Whitehead D, Grelet GA. Depth-structuring of multi-kingdom soil communities in agricultural pastures. FEMS Microbiol Ecol 2021;97:fiab156. [PMID: 34864997 DOI: 10.1093/femsec/fiab156] [Reference Citation Analysis]
6 Lam TJ, Stamboulian M, Han W, Ye Y. Model-based and phylogenetically adjusted quantification of metabolic interaction between microbial species. PLoS Comput Biol 2020;16:e1007951. [PMID: 33125363 DOI: 10.1371/journal.pcbi.1007951] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Gubert C, Kong G, Uzungil V, Zeleznikow-Johnston AM, Burrows EL, Renoir T, Hannan AJ. Microbiome Profiling Reveals Gut Dysbiosis in the Metabotropic Glutamate Receptor 5 Knockout Mouse Model of Schizophrenia. Front Cell Dev Biol 2020;8:582320. [PMID: 33195226 DOI: 10.3389/fcell.2020.582320] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
8 Venturi V, Bez C. A call to arms for cell-cell interactions between bacteria in the plant microbiome. Trends Plant Sci 2021:S1360-1385(21)00180-1. [PMID: 34334316 DOI: 10.1016/j.tplants.2021.07.007] [Reference Citation Analysis]
9 Zeng L, Dai Y, Zhang X, Man Y, Tai Y, Yang Y, Tao R. Keystone Species and Niche Differentiation Promote Microbial N, P, and COD Removal in Pilot Scale Constructed Wetlands Treating Domestic Sewage. Environ Sci Technol 2021;55:12652-63. [PMID: 34478283 DOI: 10.1021/acs.est.1c03880] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Chen L, He S, Zhai Y, Deng M. Direct interaction network inference for compositional data via codaloss. J Bioinform Comput Biol 2020;18:2050037. [PMID: 33106076 DOI: 10.1142/S0219720020500377] [Reference Citation Analysis]
11 Frioux C, Singh D, Korcsmaros T, Hildebrand F. From bag-of-genes to bag-of-genomes: metabolic modelling of communities in the era of metagenome-assembled genomes. Comput Struct Biotechnol J 2020;18:1722-34. [PMID: 32670511 DOI: 10.1016/j.csbj.2020.06.028] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 5.5] [Reference Citation Analysis]
12 Gomard Y, Flores O, Vittecoq M, Blanchon T, Toty C, Duron O, Mavingui P, Tortosa P, McCoy KD. Changes in Bacterial Diversity, Composition and Interactions During the Development of the Seabird Tick Ornithodoros maritimus (Argasidae). Microb Ecol 2021;81:770-83. [PMID: 33025063 DOI: 10.1007/s00248-020-01611-9] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Barroso-Bergadà D, Pauvert C, Vallance J, Delière L, Bohan DA, Buée M, Vacher C. Microbial networks inferred from environmental DNA data for biomonitoring ecosystem change: Strengths and pitfalls. Mol Ecol Resour 2021;21:762-80. [PMID: 33245839 DOI: 10.1111/1755-0998.13302] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
14 Aguirre de Cárcer D. Experimental and computational approaches to unravel microbial community assembly. Comput Struct Biotechnol J 2020;18:4071-81. [PMID: 33363703 DOI: 10.1016/j.csbj.2020.11.031] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
15 Brandon-Mong GJ, Shaw GT, Chen WH, Chen CC, Wang D. A network approach to investigating the key microbes and stability of gut microbial communities in a mouse neuropathic pain model. BMC Microbiol 2020;20:295. [PMID: 32998681 DOI: 10.1186/s12866-020-01981-7] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
16 Finn DR, Lee S, Lanzén A, Bertrand M, Nicol GW, Hazard C. Cropping systems impact changes in soil fungal, but not prokaryote, alpha-diversity and community composition stability over a growing season in a long-term field trial. FEMS Microbiol Ecol 2021;97:fiab136. [PMID: 34555173 DOI: 10.1093/femsec/fiab136] [Reference Citation Analysis]
17 [DOI: 10.1101/2020.07.15.195248] [Cited by in Crossref: 5] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
18 Shi Z, Xiong L, Liu T, Wu W. Alteration of bacterial communities and co-occurrence networks as a legacy effect upon exposure to polyethylene residues under field environment. J Hazard Mater 2021;426:128126. [PMID: 34954435 DOI: 10.1016/j.jhazmat.2021.128126] [Reference Citation Analysis]
19 Peschel S, Müller CL, von Mutius E, Boulesteix AL, Depner M. NetCoMi: network construction and comparison for microbiome data in R. Brief Bioinform 2021;22:bbaa290. [PMID: 33264391 DOI: 10.1093/bib/bbaa290] [Cited by in Crossref: 2] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
20 Klimenko NS, Tyakht AV, Toshchakov SV, Shevchenko MA, Korzhenkov AA, Afshinnekoo E, Mason CE, Alexeev DG. Co-occurrence patterns of bacteria within microbiome of Moscow subway. Comput Struct Biotechnol J 2020;18:314-22. [PMID: 32071708 DOI: 10.1016/j.csbj.2020.01.007] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 3.5] [Reference Citation Analysis]
21 Pettersen JP, Gundersen MS, Almaas E. Robust bacterial co-occurence community structures are independent of r- and K-selection history. Sci Rep 2021;11:23497. [PMID: 34873246 DOI: 10.1038/s41598-021-03018-z] [Reference Citation Analysis]
22 Faust K. Open challenges for microbial network construction and analysis. ISME J 2021;15:3111-8. [PMID: 34108668 DOI: 10.1038/s41396-021-01027-4] [Cited by in Crossref: 5] [Article Influence: 5.0] [Reference Citation Analysis]
23 Kawatsu K, Ushio M, van Veen FJF, Kondoh M. Are networks of trophic interactions sufficient for understanding the dynamics of multi-trophic communities? Analysis of a tri-trophic insect food-web time-series. Ecol Lett 2021;24:543-52. [PMID: 33439500 DOI: 10.1111/ele.13672] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
24 Wang Z, Usyk M, Vázquez-Baeza Y, Chen GC, Isasi CR, Williams-Nguyen JS, Hua S, McDonald D, Thyagarajan B, Daviglus ML, Cai J, North KE, Wang T, Knight R, Burk RD, Kaplan RC, Qi Q. Microbial co-occurrence complicates associations of gut microbiome with US immigration, dietary intake and obesity. Genome Biol 2021;22:336. [PMID: 34893089 DOI: 10.1186/s13059-021-02559-w] [Reference Citation Analysis]
25 Shokeen B, Dinis MDB, Haghighi F, Tran NC, Lux R. Omics and interspecies interaction. Periodontol 2000 2021;85:101-11. [PMID: 33226675 DOI: 10.1111/prd.12354] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
26 Ross BN, Whiteley M. Ignoring social distancing: advances in understanding multi-species bacterial interactions. Fac Rev 2020;9:23. [PMID: 33659955 DOI: 10.12703/r/9-23] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
27 Liu Z, Ma A, Mathé E, Merling M, Ma Q, Liu B. Network analyses in microbiome based on high-throughput multi-omics data. Brief Bioinform 2021;22:1639-55. [PMID: 32047891 DOI: 10.1093/bib/bbaa005] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]
28 Li C, Av-Shalom TV, Tan JWG, Kwah JS, Chng KR, Nagarajan N. BEEM-Static: Accurate inference of ecological interactions from cross-sectional microbiome data. PLoS Comput Biol 2021;17:e1009343. [PMID: 34495960 DOI: 10.1371/journal.pcbi.1009343] [Reference Citation Analysis]
29 Pan Z, Chen Y, Zhou M, McAllister TA, Guan LL. Microbial interaction-driven community differences as revealed by network analysis. Comput Struct Biotechnol J 2021;19:6000-8. [PMID: 34849204 DOI: 10.1016/j.csbj.2021.10.035] [Reference Citation Analysis]