Forensic identification using skin bacterial communities

By Noah Fierer, C. Lauber, N. Zhou, Daniel McDonald, E. Costello, Rob Knight. Proceedings of the National Academy of Sciences of the United States of America, 2010

662 citations recorded by the source corpus.

Subfields: Genetics, Insect Science, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0274f7a3ca67f8406c84a85009e263a8b333de45

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Citations in the corpus

The microbiota modulates gut physiology and behavioral abnormalities associated with autism (2013, positive): “Beta diversity was assessed from unweighted UniFrac, using the analysis of similarity (ANOSIM; Fierer et al., 2010), permutational multivariate analysis of variance (PERMANOVA; Anderson, 2008), permutational analysis of multivariate dispersions (PERMDISP; Anderson et al.”
Multi-Layer and Recursive Neural Networks for Metagenomic Classification (2015, neutral): “in metagenomic studies [5], [6], [22].”
A Novel Sparse Compositional Technique Reveals Microbial Perturbations (2019, methodology): “To benchmark the effectiveness of the rclr preprocessing step, we generated simulations from a study comparing microbial communities on keyboards and human ﬁngertips (keyboard data set) (19) (see Materials and Methods for details).”
EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data (2011, positive): “Although each method has limitations, these high-throughput approaches have been broadly adopted, and have provided new understanding of microbial community composition from a wide range of environments[8,11,12].”
Supervised classification of human microbiota. (2011, positive): “Correlations include, for example, diet and phylogeny in mammal guts (Ley et al ., 2008), body habitat, individual, and time in healthy adults (Costello et al ., 2009), and ﬁngertip microbiota on touched surfaces (Fierer et al ., 2010).”
Advancing our understanding of the human microbiome using QIIME (2013, background): “Panel D shows the beta-diversity PCoA plot of a data set from the “keyboard” data set (Fierer et al., 2010) which links individuals to their computer keyboard through microbial community similarity.”
Defining the Human Microbiome (2012, methodology): “PCoA plots showed that it was possible to determine which fingers were typing on which keys, and which individuals were using which keyboards: it was even possible to link a person's hand to the computer mouse they use with up to 95% accuracy when compared to a database of other hands[35].”
Cohabiting family members share microbiota with one another and with their dogs (2013, background): “via exposure to home surfaces or indoor air (both of which are typically dominated by skin-associated microbes ; Fierer et al., 2010), than it is to exchange gut or mouth bacteria, potentially because skin surfaces may be less ‘selective’ environments compared to the gut or mouth environments.”
Fingermarks, more than just a ridge pattern (2014, background): “Firstly, biomaterial can comprise human eccrine sweat, skin cells, sebaceous material, saliva and microorganism that associate human skin [1, 18].”
A Metagenomic Approach to Characterization of the Vaginal Microbiome Signature in Pregnancy (2012, methodology): “Phylogenetic trees were produced in Newick format employing interactive tree of life (iTOL) interface [56].”
The Cucurbita pepo seed microbiome: genotype-specific composition and implications for breeding (2016, methodology): “Nonparametric analyses of similarities (ANOSIM) were calculated according to Fierer et al. (2010) and Clarke (1993).”
A comprehensive evaluation of multicategory classification methods for microbiomic data (2013, neutral): “[8] [SRA: SRA0102034.”
Hidden fungi, emergent properties: endophytes and microbiomes. (2011, background): “bacterial community of the skin and digestive system is unique for each individual (36, 46).”
Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns (2010, background): “2B), even though previous work has demonstrated that adult skin communities are highly personalized and personally identifying (27), even when bacteria are transferred to touched objects (28).”