Differential analysis of microbiomes in mucus and tissues obtained from colorectal cancer patientsCOLORECTAL cancerMUCUSCANCER patientsEPITHELIAL cellsCARCINOGENESISThe outer mucus layer of the colorectal epithelium is easily removable and colonized by commensal microbiota, while the inner mucus layer is firmly...
A brief overview of methods and results for localized patterns and narrow escape 45:50 Spike patterns as a window into non-injective transient diffusive processes 37:27 Growth Control in the Drosophila Wing Imaginal Disc. 50:17 The Phase-Field-Crystal Model at Large and Small Scales 46...
That depends on the number of samples you have -- the rule of thumb is to only have about 10% of your samples. So if you have 100 samples, you should not have a formula with more than 10 variables. This measure needs to be used with caution, since the number of categories will als...
Differential analysis of membrane proteins in mouse fore- and hindbrain using a label-free approach The ability to quantitatively compare protein levels across different regions of the brain to identify disease mechanisms remains a fundamental research ch... TL Bihan,T Goh,II Stewart,... - 《Journ...
Microbiome analysis For sequence analysis, read pairs were trimmed for quality at Q15 and Illumina Nextera adapter sequences were removed using BBDuk (https://github.com/BioInfoTools/BBMap/tree/master). The pairs were subsequently assembled with the metaSPAdes pipeline from SPAdes59. Taxonomic assi...
Methods: Using next-generation sequencing analysis, we compared the VS and endometrial fluid (EF) microbiota in infertile women with (n = 20) or without CE (n = 103). Results: The detection rate of Streptococcus and Enterococcus as well as the bacterial abundance of Atopobium and ...
4. Material and Methods 4.1. Patients Our cohort included normal-weight, healthy children (group H, n = 4), and asthmatic–allergic children (n = 28) with several degrees of asthma and different body mass indexes (BMIs). Among the asthmatic–allergic children, 9 were classified as normal...
A comprehensive evaluation of microbial differential abundance analysis methods: current status and potential solutions. Microbiome 10, 130 (2022). https://doi.org/10.1186/s40168-022-01320-0 If you are interested in semi-parametric simulation for microbiome data, please refer to function "Simulate...
In the realm of medical diagnostics, particularly in differential diagnosis, where differentiating between illnesses or ailments with comparable symptoms is essential, deep learning has gained importance. Recent developments in deep learning have demonstrated considerable promise for revolutionizing medical diagno...
Because the compositional data are constrained by the simplex (sum to 1) and are not unconstrained in the Euclidean space, many standard methods of analysis are not applicable. Here, we evaluate how these challenges impact the performance of existing normalization methods and differential abundance ...