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A Diverse Community To Study Communities: Integration of Experiments and Mathematical Models To Study Microbial Consortia.

Journal of bacteriology

Succurro A, Moejes FW, Ebenhöh O.
PMID: 28533216
J Bacteriol. 2017 Jul 11;199(15). doi: 10.1128/JB.00865-16. Print 2017 Aug 01.

The last few years have seen the advancement of high-throughput experimental techniques that have produced an extraordinary amount of data. Bioinformatics and statistical analyses have become instrumental to interpreting the information coming from, e.g., sequencing data and often motivate...

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Succurro A, Moejes FW, Ebenhöh O. A Diverse Community To Study Communities: Integration of Experiments and Mathematical Models To Study Microbial Consortia. J Bacteriol. 2017;199(15)doi: 10.1128/JB.00865-16.
Succurro, A., Moejes, F. W., & Ebenhöh, O. (2017). A Diverse Community To Study Communities: Integration of Experiments and Mathematical Models To Study Microbial Consortia. Journal of bacteriology, 199(15), . https://doi.org/10.1128/JB.00865-16
Succurro, Antonella, et al. "A Diverse Community To Study Communities: Integration of Experiments and Mathematical Models To Study Microbial Consortia." Journal of bacteriology vol. 199,15 (2017). doi: https://doi.org/10.1128/JB.00865-16
Succurro A, Moejes FW, Ebenhöh O. A Diverse Community To Study Communities: Integration of Experiments and Mathematical Models To Study Microbial Consortia. J Bacteriol. 2017 Jul 11;199(15). doi: 10.1128/JB.00865-16. Print 2017 Aug 01. PMID: 28533216; PMCID: PMC5512218.
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Special Meeting Sections for the ASM Conference on Mechanisms of Interbacterial Cooperation and Competition.

Journal of bacteriology

O'Toole GA.
PMID: 29042432
J Bacteriol. 2017 Oct 17;199(22). doi: 10.1128/JB.00522-17. Print 2017 Nov 15.

No abstract available.

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O'Toole GA. Special Meeting Sections for the ASM Conference on Mechanisms of Interbacterial Cooperation and Competition. J Bacteriol. 2017;199(22)doi: 10.1128/JB.00522-17.
O'Toole, G. A. (2017). Special Meeting Sections for the ASM Conference on Mechanisms of Interbacterial Cooperation and Competition. Journal of bacteriology, 199(22), . https://doi.org/10.1128/JB.00522-17
O'Toole, George A. "Special Meeting Sections for the ASM Conference on Mechanisms of Interbacterial Cooperation and Competition." Journal of bacteriology vol. 199,22 (2017). doi: https://doi.org/10.1128/JB.00522-17
O'Toole GA. Special Meeting Sections for the ASM Conference on Mechanisms of Interbacterial Cooperation and Competition. J Bacteriol. 2017 Oct 17;199(22). doi: 10.1128/JB.00522-17. Print 2017 Nov 15. PMID: 29042432; PMCID: PMC5648862.
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Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization.

IEEE/ACM transactions on computational biology and bioinformatics

Jiang X, Hu X, Xu W, Park EK.
PMID: 26357214
IEEE/ACM Trans Comput Biol Bioinform. 2015 Mar-Apr;12(2):254-61. doi: 10.1109/TCBB.2014.2338298.

Microbial interactions play important roles on the structure and function of complex microbial communities. With the rapid accumulation of high-throughput metagenomic or 16S rRNA sequencing data, it is possible to infer complex microbial interactions. Co-occurrence patterns of microbial species...

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Jiang X, Hu X, Xu W, et al. Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization. IEEE/ACM Trans Comput Biol Bioinform. 2015;12(2):254-61doi: 10.1109/TCBB.2014.2338298.
Jiang, X., Hu, X., Xu, W., & Park, E. K. (2015). Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization. IEEE/ACM transactions on computational biology and bioinformatics, 12(2), 254-61. https://doi.org/10.1109/TCBB.2014.2338298
Jiang, Xingpeng, et al. "Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization." IEEE/ACM transactions on computational biology and bioinformatics vol. 12,2 (2015): 254-61. doi: https://doi.org/10.1109/TCBB.2014.2338298
Jiang X, Hu X, Xu W, Park EK. Predicting Microbial Interactions Using Vector Autoregressive Model with Graph Regularization. IEEE/ACM Trans Comput Biol Bioinform. 2015 Mar-Apr;12(2):254-61. doi: 10.1109/TCBB.2014.2338298. PMID: 26357214.
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Editorial overview: Host-microbe interactions: bacteria: Secretion systems, effectors, immunity and metabolism.

Current opinion in microbiology

Hartland EL, Richardson AR.
PMID: 26792669
Curr Opin Microbiol. 2016 Feb;29:v-vii. doi: 10.1016/j.mib.2015.12.003. Epub 2016 Jan 11.

No abstract available.

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Hartland EL, Richardson AR. Editorial overview: Host-microbe interactions: bacteria: Secretion systems, effectors, immunity and metabolism. Curr Opin Microbiol. 2016;29:v-viidoi: 10.1016/j.mib.2015.12.003.
Hartland, E. L., & Richardson, A. R. (2016). Editorial overview: Host-microbe interactions: bacteria: Secretion systems, effectors, immunity and metabolism. Current opinion in microbiology, 29v-vii. https://doi.org/10.1016/j.mib.2015.12.003
Hartland, Elizabeth L, and Richardson, Anthony R. "Editorial overview: Host-microbe interactions: bacteria: Secretion systems, effectors, immunity and metabolism." Current opinion in microbiology vol. 29 (2016): v-vii. doi: https://doi.org/10.1016/j.mib.2015.12.003
Hartland EL, Richardson AR. Editorial overview: Host-microbe interactions: bacteria: Secretion systems, effectors, immunity and metabolism. Curr Opin Microbiol. 2016 Feb;29:v-vii. doi: 10.1016/j.mib.2015.12.003. Epub 2016 Jan 11. PMID: 26792669.
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Auxotrophic interactions: a stabilizing attribute of aquatic microbial communities?.

FEMS microbiology ecology

Johnson WM, Alexander H, Bier RL, Miller DR, Muscarella ME, Pitz KJ, Smith H.
PMID: 32520336
FEMS Microbiol Ecol. 2020 Nov 03;96(11). doi: 10.1093/femsec/fiaa115.

Auxotrophy, or an organism's requirement for an exogenous source of an organic molecule, is widespread throughout species and ecosystems. Auxotrophy can result in obligate interactions between organisms, influencing ecosystem structure and community composition. We explore how auxotrophy-induced interactions between...

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Johnson WM, Alexander H, Bier RL, et al. Auxotrophic interactions: a stabilizing attribute of aquatic microbial communities?. FEMS Microbiol Ecol. 2020;96(11)doi: 10.1093/femsec/fiaa115.
Johnson, W. M., Alexander, H., Bier, R. L., Miller, D. R., Muscarella, M. E., Pitz, K. J., & Smith, H. (2020). Auxotrophic interactions: a stabilizing attribute of aquatic microbial communities?. FEMS microbiology ecology, 96(11), . https://doi.org/10.1093/femsec/fiaa115
Johnson, Winifred M, et al. "Auxotrophic interactions: a stabilizing attribute of aquatic microbial communities?." FEMS microbiology ecology vol. 96,11 (2020). doi: https://doi.org/10.1093/femsec/fiaa115
Johnson WM, Alexander H, Bier RL, Miller DR, Muscarella ME, Pitz KJ, Smith H. Auxotrophic interactions: a stabilizing attribute of aquatic microbial communities?. FEMS Microbiol Ecol. 2020 Nov 03;96(11). doi: 10.1093/femsec/fiaa115. PMID: 32520336; PMCID: PMC7609354.
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[Omic technologies: Current situation and future challenges].

Revista Argentina de microbiologia

Quiroga C.
PMID: 28038716
Rev Argent Microbiol. 2016 Oct - Dec;48(4):265-266. doi: 10.1016/j.ram.2016.12.001.

No abstract available.

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Quiroga C. Las tecnologías «ómicas»: situación actual y desafíos futuros. [Omic technologies: Current situation and future challenges]. Rev Argent Microbiol. 2016;48(4):265-266doi: 10.1016/j.ram.2016.12.001.
Quiroga, C. (2016). Las tecnologías «ómicas»: situación actual y desafíos futuros. [Omic technologies: Current situation and future challenges]. Revista Argentina de microbiologia, 48(4), 265-266. https://doi.org/10.1016/j.ram.2016.12.001
Quiroga, Cecilia. "Las tecnologías «ómicas»: situación actual y desafíos futuros." [Omic technologies: Current situation and future challenges]. Revista Argentina de microbiologia vol. 48,4 (2016): 265-266. doi: https://doi.org/10.1016/j.ram.2016.12.001
Quiroga C. Las tecnologías «ómicas»: situación actual y desafíos futuros. [Omic technologies: Current situation and future challenges]. Rev Argent Microbiol. 2016 Oct - Dec;48(4):265-266. doi: 10.1016/j.ram.2016.12.001. Spanish. PMID: 28038716.
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Reply to: Examining microbe-metabolite correlations by linear methods.

Nature methods

Morton JT, McDonald D, Aksenov AA, Nothias LF, Foulds JR, Quinn RA, Badri MH, Swenson TL, Van Goethem MW, Northen TR, Vazquez-Baeza Y, Wang M, Bokulich NA, Watters A, Song SJ, Bonneau R, Dorrestein PC, Knight R.
PMID: 33398188
Nat Methods. 2021 Jan;18(1):40-41. doi: 10.1038/s41592-020-01007-0. Epub 2021 Jan 04.

No abstract available.

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Morton JT, McDonald D, Aksenov AA, et al. Reply to: Examining microbe-metabolite correlations by linear methods. Nat Methods. 2021;18(1):40-41doi: 10.1038/s41592-020-01007-0.
Morton, J. T., McDonald, D., Aksenov, A. A., Nothias, L. F., Foulds, J. R., Quinn, R. A., Badri, M. H., Swenson, T. L., Van Goethem, M. W., Northen, T. R., Vazquez-Baeza, Y., Wang, M., Bokulich, N. A., Watters, A., Song, S. J., Bonneau, R., Dorrestein, P. C., & Knight, R. (2021). Reply to: Examining microbe-metabolite correlations by linear methods. Nature methods, 18(1), 40-41. https://doi.org/10.1038/s41592-020-01007-0
Morton, James T, et al. "Reply to: Examining microbe-metabolite correlations by linear methods." Nature methods vol. 18,1 (2021): 40-41. doi: https://doi.org/10.1038/s41592-020-01007-0
Morton JT, McDonald D, Aksenov AA, Nothias LF, Foulds JR, Quinn RA, Badri MH, Swenson TL, Van Goethem MW, Northen TR, Vazquez-Baeza Y, Wang M, Bokulich NA, Watters A, Song SJ, Bonneau R, Dorrestein PC, Knight R. Reply to: Examining microbe-metabolite correlations by linear methods. Nat Methods. 2021 Jan;18(1):40-41. doi: 10.1038/s41592-020-01007-0. Epub 2021 Jan 04. PMID: 33398188.
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Variability in protist grazing and growth on different marine Synechococcus isolates.

Applied and environmental microbiology

Apple JK, Strom SL, Palenik B, Brahamsha B.
PMID: 21398485
Appl Environ Microbiol. 2011 May;77(9):3074-84. doi: 10.1128/AEM.02241-10. Epub 2011 Mar 11.

Grazing mortality of the marine phytoplankton Synechococcus is dominated by planktonic protists, yet rates of consumption and factors regulating grazer-Synechococcus interactions are poorly understood. One aspect of predator-prey interactions for which little is known are the mechanisms by which...

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Apple JK, Strom SL, Palenik B, et al. Variability in protist grazing and growth on different marine Synechococcus isolates. Appl Environ Microbiol. 2011;77(9):3074-84doi: 10.1128/AEM.02241-10.
Apple, J. K., Strom, S. L., Palenik, B., & Brahamsha, B. (2011). Variability in protist grazing and growth on different marine Synechococcus isolates. Applied and environmental microbiology, 77(9), 3074-84. https://doi.org/10.1128/AEM.02241-10
Apple, Jude K, et al. "Variability in protist grazing and growth on different marine Synechococcus isolates." Applied and environmental microbiology vol. 77,9 (2011): 3074-84. doi: https://doi.org/10.1128/AEM.02241-10
Apple JK, Strom SL, Palenik B, Brahamsha B. Variability in protist grazing and growth on different marine Synechococcus isolates. Appl Environ Microbiol. 2011 May;77(9):3074-84. doi: 10.1128/AEM.02241-10. Epub 2011 Mar 11. PMID: 21398485; PMCID: PMC3126417.
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Microbial interactions: from networks to models.

Nature reviews. Microbiology

Faust K, Raes J.
PMID: 22796884
Nat Rev Microbiol. 2012 Jul 16;10(8):538-50. doi: 10.1038/nrmicro2832.

Metagenomics and 16S pyrosequencing have enabled the study of ecosystem structure and dynamics to great depth and accuracy. Co-occurrence and correlation patterns found in these data sets are increasingly used for the prediction of species interactions in environments ranging...

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Faust K, Raes J. Microbial interactions: from networks to models. Nat Rev Microbiol. 2012;10(8):538-50doi: 10.1038/nrmicro2832.
Faust, K., & Raes, J. (2012). Microbial interactions: from networks to models. Nature reviews. Microbiology, 10(8), 538-50. https://doi.org/10.1038/nrmicro2832
Faust, Karoline, and Raes, Jeroen. "Microbial interactions: from networks to models." Nature reviews. Microbiology vol. 10,8 (2012): 538-50. doi: https://doi.org/10.1038/nrmicro2832
Faust K, Raes J. Microbial interactions: from networks to models. Nat Rev Microbiol. 2012 Jul 16;10(8):538-50. doi: 10.1038/nrmicro2832. PMID: 22796884.
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Impacts of engineered nanomaterials on microbial community structure and function in natural and engineered ecosystems.

Applied microbiology and biotechnology

Mohanty A, Wu Y, Cao B.
PMID: 25109266
Appl Microbiol Biotechnol. 2014 Oct;98(20):8457-68. doi: 10.1007/s00253-014-6000-4. Epub 2014 Aug 12.

In natural and engineered environments, microorganisms often exist as complex communities, which are key to the health of ecosystems and the success of bioprocesses in various engineering applications. With the rapid development of nanotechnology in recent years, engineered nanomaterials...

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Mohanty A, Wu Y, Cao B. Impacts of engineered nanomaterials on microbial community structure and function in natural and engineered ecosystems. Appl Microbiol Biotechnol. 2014;98(20):8457-68doi: 10.1007/s00253-014-6000-4.
Mohanty, A., Wu, Y., & Cao, B. (2014). Impacts of engineered nanomaterials on microbial community structure and function in natural and engineered ecosystems. Applied microbiology and biotechnology, 98(20), 8457-68. https://doi.org/10.1007/s00253-014-6000-4
Mohanty, Anee, et al. "Impacts of engineered nanomaterials on microbial community structure and function in natural and engineered ecosystems." Applied microbiology and biotechnology vol. 98,20 (2014): 8457-68. doi: https://doi.org/10.1007/s00253-014-6000-4
Mohanty A, Wu Y, Cao B. Impacts of engineered nanomaterials on microbial community structure and function in natural and engineered ecosystems. Appl Microbiol Biotechnol. 2014 Oct;98(20):8457-68. doi: 10.1007/s00253-014-6000-4. Epub 2014 Aug 12. PMID: 25109266.
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Predicting microbial interactions through computational approaches.

Methods (San Diego, Calif.)

Li C, Lim KM, Chng KR, Nagarajan N.
PMID: 27025964
Methods. 2016 Jun 01;102:12-9. doi: 10.1016/j.ymeth.2016.02.019. Epub 2016 Mar 26.

Microorganisms play a vital role in various ecosystems and characterizing interactions between them is an essential step towards understanding the organization and function of microbial communities. Computational prediction has recently become a widely used approach to investigate microbial interactions....

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Li C, Lim KM, Chng KR, et al. Predicting microbial interactions through computational approaches. Methods. 2016;102:12-9doi: 10.1016/j.ymeth.2016.02.019.
Li, C., Lim, K. M., Chng, K. R., & Nagarajan, N. (2016). Predicting microbial interactions through computational approaches. Methods (San Diego, Calif.), 10212-9. https://doi.org/10.1016/j.ymeth.2016.02.019
Li, Chenhao, et al. "Predicting microbial interactions through computational approaches." Methods (San Diego, Calif.) vol. 102 (2016): 12-9. doi: https://doi.org/10.1016/j.ymeth.2016.02.019
Li C, Lim KM, Chng KR, Nagarajan N. Predicting microbial interactions through computational approaches. Methods. 2016 Jun 01;102:12-9. doi: 10.1016/j.ymeth.2016.02.019. Epub 2016 Mar 26. PMID: 27025964.
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Systems biology as an approach for deciphering microbial interactions.

Briefings in functional genomics

Kumar Singh P, Shukla P.
PMID: 24994863
Brief Funct Genomics. 2015 Mar;14(2):166-8. doi: 10.1093/bfgp/elu023. Epub 2014 Jul 02.

Different systems biology approaches may have a significant consequence in deciphering microbial interactions. Here, we endeavor to summarize, epigrammatic description of sophisticated techniques and software that provides an enhanced understanding of metagenomics data analysis. Apparently, such techniques are helpful...

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Kumar Singh P, Shukla P. Systems biology as an approach for deciphering microbial interactions. Brief Funct Genomics. 2014;14(2):166-8doi: 10.1093/bfgp/elu023.
Kumar Singh, P., & Shukla, P. (2015). Systems biology as an approach for deciphering microbial interactions. Briefings in functional genomics, 14(2), 166-8. https://doi.org/10.1093/bfgp/elu023
Kumar Singh, Puneet, and Shukla, Pratyoosh. "Systems biology as an approach for deciphering microbial interactions." Briefings in functional genomics vol. 14,2 (2015): 166-8. doi: https://doi.org/10.1093/bfgp/elu023
Kumar Singh P, Shukla P. Systems biology as an approach for deciphering microbial interactions. Brief Funct Genomics. 2015 Mar;14(2):166-8. doi: 10.1093/bfgp/elu023. Epub 2014 Jul 02. PMID: 24994863.
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Showing 1 to 12 of 23 entries