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Current opinion in gastroenterology.

Current opinion in gastroenterology

Walker WA.
PMID: 23010683
Curr Opin Gastroenterol. 2012 Nov;28(6):547-50. doi: 10.1097/MOG.0b013e32835955ef.

No abstract available.

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Walker WA. Current opinion in gastroenterology. Curr Opin Gastroenterol. 2012;28(6):547-50doi: 10.1097/MOG.0b013e32835955ef.
Walker, W. A. (2012). Current opinion in gastroenterology. Current opinion in gastroenterology, 28(6), 547-50. https://doi.org/10.1097/MOG.0b013e32835955ef
Walker, W Allan. "Current opinion in gastroenterology." Current opinion in gastroenterology vol. 28,6 (2012): 547-50. doi: https://doi.org/10.1097/MOG.0b013e32835955ef
Walker WA. Current opinion in gastroenterology. Curr Opin Gastroenterol. 2012 Nov;28(6):547-50. doi: 10.1097/MOG.0b013e32835955ef. PMID: 23010683.
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An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS.

Methods in molecular biology (Clifton, N.J.)

Silva GGZ, Lopes FAC, Edwards RA.
PMID: 28451970
Methods Mol Biol. 2017;1611:35-44. doi: 10.1007/978-1-4939-7015-5_4.

One of the main goals in metagenomics is to identify the functional profile of a microbial community from unannotated shotgun sequencing reads. Functional annotation is important in biological research because it enables researchers to identify the abundance of functional...

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Silva GGZ, Lopes FAC, Edwards RA. An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS. Methods Mol Biol. 2017;1611:35-44doi: 10.1007/978-1-4939-7015-5_4.
Silva, G. G. Z., Lopes, F. A. C., & Edwards, R. A. (2017). An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS. Methods in molecular biology (Clifton, N.J.), 161135-44. https://doi.org/10.1007/978-1-4939-7015-5_4
Silva, Genivaldo Gueiros Z, et al. "An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS." Methods in molecular biology (Clifton, N.J.) vol. 1611 (2017): 35-44. doi: https://doi.org/10.1007/978-1-4939-7015-5_4
Silva GGZ, Lopes FAC, Edwards RA. An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS. Methods Mol Biol. 2017;1611:35-44. doi: 10.1007/978-1-4939-7015-5_4. PMID: 28451970.
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Snowball: strain aware gene assembly of metagenomes.

Bioinformatics (Oxford, England)

Gregor I, Schönhuth A, McHardy AC.
PMID: 27587685
Bioinformatics. 2016 Sep 01;32(17):i649-i657. doi: 10.1093/bioinformatics/btw426.

MOTIVATION: Gene assembly is an important step in functional analysis of shotgun metagenomic data. Nonetheless, strain aware assembly remains a challenging task, as current assembly tools often fail to distinguish among strain variants or require closely related reference genomes...

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Gregor I, Schönhuth A, McHardy AC. Snowball: strain aware gene assembly of metagenomes. Bioinformatics. 2016;32(17):i649-i657doi: 10.1093/bioinformatics/btw426.
Gregor, I., Schönhuth, A., & McHardy, A. C. (2016). Snowball: strain aware gene assembly of metagenomes. Bioinformatics (Oxford, England), 32(17), i649-i657. https://doi.org/10.1093/bioinformatics/btw426
Gregor, I, et al. "Snowball: strain aware gene assembly of metagenomes." Bioinformatics (Oxford, England) vol. 32,17 (2016): i649-i657. doi: https://doi.org/10.1093/bioinformatics/btw426
Gregor I, Schönhuth A, McHardy AC. Snowball: strain aware gene assembly of metagenomes. Bioinformatics. 2016 Sep 01;32(17):i649-i657. doi: 10.1093/bioinformatics/btw426. PMID: 27587685.
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Current drug metabolism.

Current drug metabolism

Huang CM.
PMID: 19149507
Curr Drug Metab. 2009 Jan;10(1):1. doi: 10.2174/138920009787048400.

No abstract available.

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Huang CM. Current drug metabolism. Curr Drug Metab. 2009;10(1):1doi: 10.2174/138920009787048400.
Huang, C. M. (2009). Current drug metabolism. Current drug metabolism, 10(1), 1. https://doi.org/10.2174/138920009787048400
Huang, Chun-Ming. "Current drug metabolism." Current drug metabolism vol. 10,1 (2009): 1. doi: https://doi.org/10.2174/138920009787048400
Huang CM. Current drug metabolism. Curr Drug Metab. 2009 Jan;10(1):1. doi: 10.2174/138920009787048400. PMID: 19149507.
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Bioinformatics for the Human Microbiome Project.

PLoS computational biology

Gevers D, Pop M, Schloss PD, Huttenhower C.
PMID: 23209389
PLoS Comput Biol. 2012;8(11):e1002779. doi: 10.1371/journal.pcbi.1002779. Epub 2012 Nov 29.

No abstract available.

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Gevers D, Pop M, Schloss PD, et al. Bioinformatics for the Human Microbiome Project. PLoS Comput Biol. 2012;8(11):e1002779doi: 10.1371/journal.pcbi.1002779.
Gevers, D., Pop, M., Schloss, P. D., & Huttenhower, C. (2012). Bioinformatics for the Human Microbiome Project. PLoS computational biology, 8(11), e1002779. https://doi.org/10.1371/journal.pcbi.1002779
Gevers, Dirk, et al. "Bioinformatics for the Human Microbiome Project." PLoS computational biology vol. 8,11 (2012): e1002779. doi: https://doi.org/10.1371/journal.pcbi.1002779
Gevers D, Pop M, Schloss PD, Huttenhower C. Bioinformatics for the Human Microbiome Project. PLoS Comput Biol. 2012;8(11):e1002779. doi: 10.1371/journal.pcbi.1002779. Epub 2012 Nov 29. PMID: 23209389; PMCID: PMC3510052.
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Tackling the microbiome.

Science (New York, N.Y.)

Hood L.
PMID: 22674329
Science. 2012 Jun 08;336(6086):1209. doi: 10.1126/science.1225475. Epub 2012 Jun 06.

No abstract available.

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Hood L. Tackling the microbiome. Science. 2012;336(6086):1209doi: 10.1126/science.1225475.
Hood, L. (2012). Tackling the microbiome. Science (New York, N.Y.), 336(6086), 1209. https://doi.org/10.1126/science.1225475
Hood, Leroy. "Tackling the microbiome." Science (New York, N.Y.) vol. 336,6086 (2012): 1209. doi: https://doi.org/10.1126/science.1225475
Hood L. Tackling the microbiome. Science. 2012 Jun 08;336(6086):1209. doi: 10.1126/science.1225475. Epub 2012 Jun 06. PMID: 22674329.
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The microbiota in respiratory disease.

American journal of respiratory and critical care medicine

Erb-Downward JR, Huffnagle GB, Martinez FJ.
PMID: 22589308
Am J Respir Crit Care Med. 2012 May 15;185(10):1037-8. doi: 10.1164/rccm.201203-0567ED.

No abstract available.

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Erb-Downward JR, Huffnagle GB, Martinez FJ. The microbiota in respiratory disease. Am J Respir Crit Care Med. 2012;185(10):1037-8doi: 10.1164/rccm.201203-0567ED.
Erb-Downward, J. R., Huffnagle, G. B., & Martinez, F. J. (2012). The microbiota in respiratory disease. American journal of respiratory and critical care medicine, 185(10), 1037-8. https://doi.org/10.1164/rccm.201203-0567ED
Erb-Downward, John R, et al. "The microbiota in respiratory disease." American journal of respiratory and critical care medicine vol. 185,10 (2012): 1037-8. doi: https://doi.org/10.1164/rccm.201203-0567ED
Erb-Downward JR, Huffnagle GB, Martinez FJ. The microbiota in respiratory disease. Am J Respir Crit Care Med. 2012 May 15;185(10):1037-8. doi: 10.1164/rccm.201203-0567ED. PMID: 22589308.
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Computational systems biology and in silico modeling of the human microbiome.

Briefings in bioinformatics

Borenstein E.
PMID: 22589385
Brief Bioinform. 2012 Nov;13(6):769-80. doi: 10.1093/bib/bbs022. Epub 2012 May 15.

The human microbiome is a complex biological system with numerous interacting components across multiple organizational levels. The assembly, ecology and dynamics of the microbiome and its contribution to the development, physiology and nutrition of the host are clearly affected...

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Borenstein E. Computational systems biology and in silico modeling of the human microbiome. Brief Bioinform. 2012;13(6):769-80doi: 10.1093/bib/bbs022.
Borenstein, E. (2012). Computational systems biology and in silico modeling of the human microbiome. Briefings in bioinformatics, 13(6), 769-80. https://doi.org/10.1093/bib/bbs022
Borenstein, Elhanan. "Computational systems biology and in silico modeling of the human microbiome." Briefings in bioinformatics vol. 13,6 (2012): 769-80. doi: https://doi.org/10.1093/bib/bbs022
Borenstein E. Computational systems biology and in silico modeling of the human microbiome. Brief Bioinform. 2012 Nov;13(6):769-80. doi: 10.1093/bib/bbs022. Epub 2012 May 15. PMID: 22589385.
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Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification.

PloS one

Pongor LS, Vera R, Ligeti B.
PMID: 25077800
PLoS One. 2014 Jul 31;9(7):e103441. doi: 10.1371/journal.pone.0103441. eCollection 2014.

Next generation sequencing (NGS) of metagenomic samples is becoming a standard approach to detect individual species or pathogenic strains of microorganisms. Computer programs used in the NGS community have to balance between speed and sensitivity and as a result,...

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Pongor LS, Vera R, Ligeti B. Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification. PLoS One. 2014;9(7):e103441doi: 10.1371/journal.pone.0103441.
Pongor, L. S., Vera, R., & Ligeti, B. (2014). Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification. PloS one, 9(7), e103441. https://doi.org/10.1371/journal.pone.0103441
Pongor, Lőrinc S, et al. "Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification." PloS one vol. 9,7 (2014): e103441. doi: https://doi.org/10.1371/journal.pone.0103441
Pongor LS, Vera R, Ligeti B. Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification. PLoS One. 2014 Jul 31;9(7):e103441. doi: 10.1371/journal.pone.0103441. eCollection 2014. PMID: 25077800; PMCID: PMC4117525.
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The uses of race and ethnicity in human microbiome research.

Trends in microbiology

Fortenberry JD.
PMID: 23566633
Trends Microbiol. 2013 Apr;21(4):165-6. doi: 10.1016/j.tim.2013.01.001.

Research on the human microbiome is beginning to address factors associated with between-group differences. Recognition of the social and political nature of traditional race and ethnicity categories will allow microbiome research to contribute to reduction of health disparities while...

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Fortenberry JD. The uses of race and ethnicity in human microbiome research. Trends Microbiol. 2013;21(4):165-6doi: 10.1016/j.tim.2013.01.001.
Fortenberry, J. D. (2013). The uses of race and ethnicity in human microbiome research. Trends in microbiology, 21(4), 165-6. https://doi.org/10.1016/j.tim.2013.01.001
Fortenberry, J Dennis. "The uses of race and ethnicity in human microbiome research." Trends in microbiology vol. 21,4 (2013): 165-6. doi: https://doi.org/10.1016/j.tim.2013.01.001
Fortenberry JD. The uses of race and ethnicity in human microbiome research. Trends Microbiol. 2013 Apr;21(4):165-6. doi: 10.1016/j.tim.2013.01.001. PMID: 23566633.
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Fragment recruitment on metabolic pathways: comparative metabolic profiling of metagenomes and metatranscriptomes.

Bioinformatics (Oxford, England)

Desai DK, Schunck H, Löser JW, Laroche J.
PMID: 23303511
Bioinformatics. 2013 Mar 15;29(6):790-1. doi: 10.1093/bioinformatics/bts721. Epub 2013 Jan 09.

MOTIVATION: The sheer scale of the metagenomic and metatranscriptomic datasets that are now available warrants the development of automated protocols for organizing, annotating and comparing the samples in terms of their metabolic profiles. We describe a user-friendly java program...

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Desai DK, Schunck H, Löser JW, et al. Fragment recruitment on metabolic pathways: comparative metabolic profiling of metagenomes and metatranscriptomes. Bioinformatics. 2013;29(6):790-1doi: 10.1093/bioinformatics/bts721.
Desai, D. K., Schunck, H., Löser, J. W., & Laroche, J. (2013). Fragment recruitment on metabolic pathways: comparative metabolic profiling of metagenomes and metatranscriptomes. Bioinformatics (Oxford, England), 29(6), 790-1. https://doi.org/10.1093/bioinformatics/bts721
Desai, Dhwani K, et al. "Fragment recruitment on metabolic pathways: comparative metabolic profiling of metagenomes and metatranscriptomes." Bioinformatics (Oxford, England) vol. 29,6 (2013): 790-1. doi: https://doi.org/10.1093/bioinformatics/bts721
Desai DK, Schunck H, Löser JW, Laroche J. Fragment recruitment on metabolic pathways: comparative metabolic profiling of metagenomes and metatranscriptomes. Bioinformatics. 2013 Mar 15;29(6):790-1. doi: 10.1093/bioinformatics/bts721. Epub 2013 Jan 09. PMID: 23303511.
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Sequencing the gut metagenome as a noninvasive diagnosis for advanced nonalcoholic steatohepatitis.

Hepatology (Baltimore, Md.)

Zhu L, Baker RD, Zhu R, Baker SS.
PMID: 28732121
Hepatology. 2017 Dec;66(6):2080-2083. doi: 10.1002/hep.29387. Epub 2017 Oct 30.

No abstract available.

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Zhu L, Baker RD, Zhu R, et al. Sequencing the gut metagenome as a noninvasive diagnosis for advanced nonalcoholic steatohepatitis. Hepatology. 2017;66(6):2080-2083doi: 10.1002/hep.29387.
Zhu, L., Baker, R. D., Zhu, R., & Baker, S. S. (2017). Sequencing the gut metagenome as a noninvasive diagnosis for advanced nonalcoholic steatohepatitis. Hepatology (Baltimore, Md.), 66(6), 2080-2083. https://doi.org/10.1002/hep.29387
Zhu, Lixin, et al. "Sequencing the gut metagenome as a noninvasive diagnosis for advanced nonalcoholic steatohepatitis." Hepatology (Baltimore, Md.) vol. 66,6 (2017): 2080-2083. doi: https://doi.org/10.1002/hep.29387
Zhu L, Baker RD, Zhu R, Baker SS. Sequencing the gut metagenome as a noninvasive diagnosis for advanced nonalcoholic steatohepatitis. Hepatology. 2017 Dec;66(6):2080-2083. doi: 10.1002/hep.29387. Epub 2017 Oct 30. PMID: 28732121.
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Showing 1 to 12 of 100 entries