RESUMEN
In the age of long read sequencing, genomics researchers now have access to accurate repetitive DNA sequence (including satellites) that, due to the limitations of short read sequencing, could previously be observed only as unmappable fragments. Tools that annotate repetitive sequence are now more important than ever, so that we can better understand newly uncovered repetitive sequences, and also so that we can mitigate errors in bioinformatic software caused by those repetitive sequences. To that end, we introduce the 1.0 release of our tool for identifying and annotating locally-repetitive sequence, ULTRA (ULTRA Locates Tandemly Repetitive Areas). ULTRA is fast enough to use as part of an efficient annotation pipeline, produces state-of-the-art reliable coverage of repetitive regions containing many mutations, and provides interpretable statistics and labels for repetitive regions. It released under an open license, and available for download at https://github.com/TravisWheelerLab/ULTRA.
RESUMEN
The SARS-CoV2 pandemic has highlighted the importance of efficient and effective methods for identification of therapeutic drugs, and in particular has laid bare the need for methods that allow exploration of the full diversity of synthesizable small molecules. While classical high-throughput screening methods may consider up to millions of molecules, virtual screening methods hold the promise of enabling appraisal of billions of candidate molecules, thus expanding the search space while concurrently reducing costs and speeding discovery. Here, we describe a new screening pipeline, called drugsniffer, that is capable of rapidly exploring drug candidates from a library of billions of molecules, and is designed to support distributed computation on cluster and cloud resources. As an example of performance, our pipeline required â¼40,000 total compute hours to screen for potential drugs targeting three SARS-CoV2 proteins among a library of â¼3.7 billion candidate molecules.
RESUMEN
An automated analytical system has been implemented for the high-throughput optimization of processing conditions such as curing parameters in fabrication of UV-cured automotive organic protective coatings. Selection of optimum process conditions of combinatorial arrays of coatings is essential to correlate the high-throughput screening and conventional processes and to achieve the desired physical properties of coatings. For monitoring of curing conditions of each coating in the array, a viscosity-sensitive fluorophore 4,4'-bis(2-benzoxazolyl)stilbene was incorporated into coating formulations. This fluorescence tagging approach permitted us to combine a gradient temperature heater and a UV curing system with the full capabilities of our high-throughput screening system, including generation of spectroscopic data and its analysis. This investigation demonstrated the possibility of rapid decoupling of temperature and radiation effects in curing of UV-curable coating formulations by using multiple coatings and process conditions at once. While the system described here was implemented for high-throughput optimization of temperature conditions of radiation curing of arrays of organic protective coatings for automotive applications, this system can be further applied for a variety of other applications where optimization of process parameters can be studied in situ or off-line using optical spectroscopic tools.
RESUMEN
Design, validation, and implementation of an optical spectroscopic system for high-throughput analysis of combinatorially developed protective organic coatings are reported. Our approach replaces labor-intensive coating evaluation steps with an automated system that rapidly analyzes 8 x 6 arrays of coating elements that are discretely deposited on a single plastic substrate. Each coating element of the library is 10 mm in diameter and 2-5 microm thick. Performance of coatings is evaluated with respect to their resistance to wear abrasion because this parameter is one of the primary considerations in end-use applications. Upon testing, the coating materials undergo changes that are impossible to quantitatively predict using existing knowledge. Coatings are abraded using industry-accepted abrasion test methods at a single or multiple abrasion conditions followed by the high-throughput analysis of abrasion-induced light scatter. The developed automated system is optimized for the analysis of diffusively scattered light that corresponds to 0-30% haze. System precision of 0.1-2.5% relative standard deviation provides capability for the reliable ranking of coatings performance. Although the system was implemented for high-throughput screening of combinatorially developed organic protective coatings for automotive applications, it can be applied for a variety of other applications for which materials ranking can be achieved using optical spectroscopic tools.
