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Yale Journal of Biology and Medicine, ISSN 0044-0086, 09/2016, Volume 89, Issue 3, pp. 275 - 276
Journal Article
Cell host & microbe, ISSN 1931-3128, 2018, Volume 24, Issue 1, pp. 133 - 145.e5
Journal Article
BMC microbiology, ISSN 1471-2180, 2017, Volume 17, Issue 1, pp. 194 - 16
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 | Prebiotics | Studies | Reproducibility | Relative abundance | Quality control | Genetic testing | Methods
Journal Article
Nature (London), ISSN 1476-4687, 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 | rRNA 16S | Breastfeeding & lactation | Taxonomy | Crosstalk | Microbiomes | Families & family life | Infants | Diabetes mellitus (insulin dependent) | Birth | Phase transitions | Gene sequencing | Microorganisms | Microbiota | Age | Geographical distribution | Maturation | Diabetes mellitus | Environmental factors | Breast feeding | Metabolism | Multiculturalism & pluralism | Asthma | Babies | Antibiotics | Autoimmune diseases | Breast milk | Structure-function relationships | 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
Microbiome, ISSN 2049-2618, 2018, Volume 6, Issue 1, pp. 72 - 11
Background: Gut microbes influence their hosts in many ways, in particular by modulating the impact of diet. These effects have been studied most extensively... 
Human microbiome | Pig microbiome | Metagenomics | Diet | Dog microbiome | Mouse microbiome | Microbiome | WEIGHT-LOSS | MICROBIOLOGY | MODEL | LOW-CARBOHYDRATE | ABUNDANCE | OBESITY | MICROBES | CATALOG | HIGH-PROTEIN | NUTRITION | Feces - microbiology | Obesity | Microbiota | Animals | Swine | Humans | Dogs | Gastrointestinal Microbiome | Metagenomics - methods | Mice | Metagenome | Genetic research | Genes | Genomics
Journal Article