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Nature reviews. Gastroenterology & hepatology, ISSN 1759-5045, 06/2019, Volume 16, Issue 7, pp. 448 - 448
An amendment to this paper has been published and can be accessed via a link at the top of the paper. 
Microbiomes
Journal Article
Nature, ISSN 0028-0836, 02/2019, Volume 566, Issue 7744, pp. 299 - 299
Journal Article
Yale Journal of Biology and Medicine, ISSN 0044-0086, 09/2016, Volume 89, Issue 3, pp. 275 - 276
Journal Article
12/2016, ISBN 9781118801413
Book
05/2017, Hui: Food Science and Technology, ISBN 1119098831, 353
Now in a revised second edition, Nutrigenomics and Proteomics in Health and Disease brings together the very latest science based upon nutrigenomics and... 
TECHNOLOGY & ENGINEERING / Food Science
eBook
Scientific reports, ISSN 2045-2322, 06/2019, Volume 9, Issue 1, pp. 8571 - 1
A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper. 
Microbiomes
Journal Article
PLoS biology, ISSN 1544-9173, 11/2018, Volume 16, Issue 11, pp. e2005396 - e2005396
Journal Article
Cell Host & Microbe, ISSN 1931-3128, 07/2018, Volume 24, Issue 1, pp. 133 - 145.e5
Journal Article
Nature Biotechnology, ISSN 1087-0156, 09/2019, Volume 37, Issue 9, pp. 1091 - 1091
An amendment to this paper has been published and can be accessed via a link at the top of the paper. 
Microbiomes | Index Medicus
Journal Article
BMC Microbiology, ISSN 1471-2180, 09/2017, Volume 17, Issue 1, pp. 194 - 194
Background: Advancements in Next Generation Sequencing (NGS) technologies regarding throughput, read length and accuracy had a major impact on microbiome... 
Bioinformatics pipeline | NGS bias | 16S rRNA amplicon sequencing - microbiome analysis - microbiome - microbiome composition - next generation sequencing platforms | BACTERIA | OLIGOSACCHARIDES | BIAS | next generation sequencing platforms | PROBIOTICS | MICROBIOLOGY | ILLUMINA | microbiome analysis | microbiome | IMPACT | microbiome composition | TECHNOLOGIES | 16S rRNA amplicon sequencing | Multivariate Analysis | Computational Biology - methods | Reproducibility of Results | DNA, Bacterial - isolation & purification | Gene Library | Computational Biology - instrumentation | Chickens - microbiology | Statistics as Topic | Cecum - microbiology | Phylogeny | Biodiversity | Gastrointestinal Microbiome - genetics | Bacteria - genetics | Animals | DNA, Bacterial - genetics | Analysis of Variance | Base Sequence | Bacteria - classification | RNA, Ribosomal, 16S - genetics | DNA, Bacterial - analysis | Microbial Consortia - genetics | High-Throughput Nucleotide Sequencing - instrumentation | High-Throughput Nucleotide Sequencing - methods | RNA sequencing | Genetic aspects | Comparative analysis | Microbial colonies | Performance evaluation | rRNA 16S | Laboratories | Pipelines | Picking | Genomics | Bias | Genomes | Species diversity | Taxa | Biological effects | Microorganisms | Bioinformatics | Deoxyribonucleic acid--DNA | Platforms | Data analysis | Filtration | Cecum | Data processing | Abundance | Biological diversity | Prebiotics | Studies | Reproducibility | Relative abundance | Quality control | Genetic testing | Methods | Index Medicus
Journal Article
2018, ISBN 9782889455058
In complex systems, such as our body or a plant, the host is living together with thousands of microbes, which support the entire system in function and... 
mycobiome | human microbiome | microbial interplay | built environment | animal microbiome | microbiome control | plant microbiome | Microbiome
eBook
British Journal of Dermatology, ISSN 0007-0963, 09/2019, Volume 181, Issue 3, pp. 444 - 445
Linked Article : Prast‐Nielsen et al . Br J Dermatol 2019; 181 :572–579 . 
Skin | Microbiomes | Index Medicus
Journal Article
EMBO reports, ISSN 1469-221X, 03/2019, Volume 20, Issue 3, p. n/a
Anti‐vaccine activists misuse findings from microbiome research to push their agenda. It requires a concerted response by the scientific community to confront... 
Vaccination | Microbiomes | Vaccines
Journal Article
EMBO reports, ISSN 1469-221X, 06/2018, Volume 19, Issue 6, p. n/a
Our project to engage members of the public with metagenomics of microbiota in their households yielded interesting results about their perception of health... 
Microbiota | Households | Hygiene | Microbiomes
Journal Article
Archives of Toxicology, ISSN 0340-5761, 07/2019, pp. 1 - 2
Journal Article
Nature, ISSN 0028-0836, 10/2018, Volume 562, Issue 7728, pp. 583 - 588
The development of the microbiome from infancy to childhood is dependent on a range of factors, with microbial-immune crosstalk during this time thought to be... 
INTESTINAL MICROBIOTA | KYOTO ENCYCLOPEDIA | MULTIDISCIPLINARY SCIENCES | ENVIRONMENTAL DETERMINANTS | DISEASE | RISK | QUALITY-CONTROL | INFANT | ESTABLISHMENT | BREAST-MILK | EXPOSURE | Humans | Child, Preschool | Firmicutes - genetics | Infant | Male | Gastrointestinal Microbiome - physiology | Bifidobacterium - isolation & purification | Case-Control Studies | Time Factors | Diabetes Mellitus, Type 1 - microbiology | Female | Surveys and Questionnaires | Diabetes Mellitus, Type 1 - immunology | Child | Siblings | Datasets as Topic | Firmicutes - isolation & purification | Bifidobacterium - classification | Bifidobacterium - genetics | Firmicutes - classification | Breast Feeding - statistics & numerical data | Gastrointestinal Microbiome - genetics | Pets | Animals | Adolescent | RNA, Ribosomal, 16S - genetics | Gastrointestinal Microbiome - immunology | Milk, Human - immunology | Milk, Human - microbiology | Cluster Analysis | Medical research | Microbiota (Symbiotic organisms) | Environmental aspects | Medicine, Experimental | Development and progression | Research | Diabetes | Children | Health aspects | Autoimmunity | RNA | Breast feeding | Type 1 diabetes | Analysis | rRNA 16S | Breastfeeding & lactation | Taxonomy | Crosstalk | Microbiomes | Families & family life | Infants | Diabetes mellitus (insulin dependent) | Birth | Gene sequencing | Microorganisms | Microbiota | Age | Geographical distribution | Phase transformations | Maturation | Diabetes mellitus | Environmental factors | Metabolism | Multiculturalism & pluralism | Asthma | Babies | Antibiotics | Autoimmune diseases | Breast milk | Structure-function relationships | Index Medicus | Basic Medicine | Medical and Health Sciences | Microbiology in the medical area | Mikrobiologi inom det medicinska området | Medicin och hälsovetenskap | Medicinska och farmaceutiska grundvetenskaper
Journal Article
Nature, ISSN 0028-0836, 10/2018, Volume 562, Issue 7728, pp. 589 - 594
Type 1 diabetes (T1D) is an autoimmune disease that targets pancreatic islet beta cells and incorporates genetic and environmental factors(1), including... 
RISK-FACTORS | INTESTINAL MICROBIOTA | AUTOIMMUNITY | YOUNG TEDDY | MULTIDISCIPLINARY SCIENCES | ENVIRONMENTAL DETERMINANTS | SEQUENCE | DYNAMICS | ASSOCIATION | CONTRIBUTES | CHILDREN | Diabetes Mellitus, Type 1 - epidemiology | Fatty Acids, Volatile - pharmacology | Diabetes Mellitus, Type 1 - prevention & control | Humans | Breast Feeding | Child, Preschool | Infant | Male | Gastrointestinal Microbiome - physiology | Bifidobacterium - isolation & purification | Proteobacteria - genetics | Feces - microbiology | Diabetes Mellitus, Type 1 - microbiology | Female | Disease Models, Animal | Bifidobacterium - genetics | Diabetes Mellitus, Type 1 - genetics | Islets of Langerhans - immunology | European Continental Ancestry Group | Gastrointestinal Microbiome - genetics | Animals | Health Surveys | Proteobacteria - isolation & purification | Age of Onset | Bifidobacterium - enzymology | Mice | Gastrointestinal Microbiome - immunology | Milk, Human - immunology | Milk, Human - microbiology | Longitudinal Studies | Proteobacteria - enzymology | Genetic aspects | Research | Diabetes | Microbiota (Symbiotic organisms) | Diabetes in children | Type 2 diabetes | Autoimmunity | Pancreatic beta cells | Type 1 diabetes | Analysis | Infants | Breast feeding | Fatty acids | Taxonomy | Genes | Microbiomes | Chains | Genomes | Diabetes mellitus (insulin dependent) | Biosynthesis | Microorganisms | Microbiota | Children | Pancreas | Bioinformatics | Age | Diabetes mellitus