1,894 research outputs found
Git for Data Analysis – why version control is essential for collaboration and for gaining public trust
Openness and collaboration go hand in hand. Samuel Payne describes how scientists at the Pacific Northwest National Laboratory are working with the Frictionless Data team at Open Knowledge International to ensure collaboration on data analysis is seamless and their data integrity is maintained
Proteogenomic Analysis of Bacteria and Archaea: A 46 Organism Case Study
Experimental evidence is increasingly being used to reassess the quality and accuracy of genome annotation. Proteomics data used for this purpose, called proteogenomics, can alleviate many of the problematic areas of genome annotation, e.g. short protein validation and start site assignment. We performed a proteogenomic analysis of 46 genomes spanning eight bacterial and archaeal phyla across the tree of life. These diverse datasets facilitated the development of a robust approach for proteogenomics that is functional across genomes varying in %GC, gene content, proteomic sampling depth, phylogeny, and genome size. In addition to finding evidence for 682 novel proteins, 1336 new start sites, and numerous dubious genes, we discovered sites of post-translational maturation in the form of proteolytic cleavage of 1175 signal peptides. The number of novel proteins per genome is highly variable (median 7, mean 15, stdev 20). Moreover, comparison of novel genes with the current genes did not reveal any consistent abnormalities. Thus, we conclude that proteogenomics fulfills a yet to be understood deficiency in gene prediction. With the adoption of new sequencing technologies which have higher error rates than Sanger-based methods and the advances in proteomics, proteogenomics may become even more important in the future
Sizing individual dielectric nanoparticles with quantitative differential interference contrast microscopy
We report a method to measure the size of single dielectric nanoparticles
with high accuracy and precision using quantitative differential interference
contrast (DIC) microscopy. Dielectric nanoparticles are detected optically by
the conversion of the optical phase change into an intensity change using DIC.
Phase images of individual nanoparticles were retrieved from DIC by Wiener
filtering, and a quantitative methodology to extract nanoparticle sizes was
developed. Using polystyrene beads of 100 nm radius as size standard, we show
that the method determines this radius within a few nm accuracy. The smallest
detectable polystyrene bead is limited by background and shot-noise, which
depend on acquisition and analysis parameters, including the objective
numerical aperture, the DIC phase offset, and the refractive index contrast
between particles and their surrounding. A sensitivity limit potentially
reaching down to 1.8 nm radius was inferred. As application example, individual
nanodiamonds with nominal sizes below 50 nm were measured, and were found to
have a nearly exponential size distribution with 28 nm mean value. Considering
the importance of dielectric nanoparticles in many fields, from naturally
occurring virions to polluting nanoplastics, the proposed method could offer a
powerful quantitative tool for nanoparticle analysis, combining accuracy,
sensitivity and high-throughput with widely available and easy-to-use DIC
microscop
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