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1,661 results for “Throughput”
Data and Code for: Validating ATLAS: a regional-scale high-throughput tracking system
<p>Data and code for the manuscript: <strong>Validating ATLAS: a regional-scale high-throughput tracking system</strong></p>
High-throughput event-based and frame-based convolutions for event-cameras
<p>Event cameras are promising sensors for on-line and real-time vision tasks, due to their high temporal resolution, low latency and the elimination of redundant static data. Many vision algorithms use some form of spatial convolution (i.e. spatial pattern detection) as a fundamental component, but additional consideration must be taken for event cameras, as the visual signal is asynchronous and sparse. While elegant methods have been proposed for event-based convolutions, they are unsuitable for real scenarios due to their inefficient processing pipeline, and subsequent low event-throughput. This paper presents an efficient implementation based on decoupling the event-based computations from the computationally heavy convolution ones, increasing the maximum event processing rate by 15.92x, to over 10 million events/second, while still maintaining the event-based paradigm of asynchronous input and output. Results on public datasets with modern 640x480 event-camera recordings show that the proposed implementation achieves real-time processing with minimal impact in the convolution result, while the prior state-of-the-art results in latency of over 1 second per-event.</p>
A high-throughput assay for quantifying phenotypic traits of microalgae
<p>High-throughput methods for phenotyping microalgae are in demand across a variety of research and commercial purposes. Many microalgae can be readily cultivated in multi-well plates for experimental studies which can reduce overall costs, while measuring traits from low volume samples can reduce handling. Here we develop a high-throughput quantitative phenotypic assay (QPA) that can be used to phenotype microalgae grown in multi-well plates. The QPA integrates 10 low-volume, relatively high-throughput trait measurements (growth rate, cell size, granularity, chlorophyll a, neutral lipid content, silicification, reactive oxygen species accumulation, and photophysiology parameters: ETRmax, Ik, and alpha) into one workflow. We demonstrate the utility of the QPA on Thalassiosira spp., a cosmopolitan marine diatom, phenotyping six strains in a standard nutrient rich environment (f/2 media) using the full 10-trait assay. The multivariate phenotypes of strains can be simplified into two dimensions using principal component analysis, generating a trait-scape. We determine that traits show a consistent pattern when grown in small volume compared to more typical large volumes. The QPA can thus be used for quantifying traits across different growth environments without requiring exhaustive large-scale culturing experiments, which facilitates experiments on trait plasticity. We confirm that this assay can be used to phenotype newly isolated diatom strains within 4 weeks of isolation. The QPA described here is highly amenable to customisation for other traits or unicellular taxa and provides a framework for designing high-throughput experiments. This method will have applications in experimental evolution, modelling, and for commercial applications where screening of phytoplankton traits is of high importance.</p>
A Framework for High-throughput Sequence Alignment using Real Processing-in-Memory Systems
<p>Sequence alignment is a fundamentally memory bound computation whose performance in modern systems is limited by the memory bandwidth bottleneck. Processing-in-memory architectures alleviate this bottleneck by providing the memory with computing competencies. We propose Alignment-in-Memory (AIM), a framework for high-throughput sequence alignment using processing-in-memory, and evaluate it on UPMEM, the first publicly-available general-purpose programmable processing-in-memory system.</p>
Precalculated Results of Throughput Analysis in "Comprehensive Benchmarking of High-Performance Vector Field Representations"
<p>This repository contains results calculated by our throughput analysis. These results should be exactly and deterministically reproducible using the aforementioned software, but precomputed results are provided for the benefit of the reader, in case certain software is not available. Included in this artifact are the assembly files generated by the compilers, the throughput analysis of these aforementioned assembly files, and a collection of tables which summarize the results.</p> <p>These results were generated using <em>clang</em> version 14.0.6, <em>gcc</em> version 11.2.0, and <em>llvm-mca</em> version 14.0.6.</p>
Raw Data of the plots presented in the article entitled "Minute-Made, High-Efficiency Nanostructured Bi2Te3 via High-Throughput Green Solution Chemical Synthesis"
<p>This is the collection of raw data for the graphical items presented in the article with given details. </p> <p>This research has received funding from the Swedish Energy Agency (43521-1) and in part by Swedish Research Agency Council (VR, 2018-03462) and the European Union’s Horizon 2020 research and innovation program under the grant agreement No 863222.</p>
Bayesian Estimation on Microbial Electrochemical Time Profiles obtained by a High-Throughput Bioelectrochemical Device
<p>Bioelectrochemical systems (BESs) are attracting much attention, but the mechanisms are not yet fully clarified. One of the issues for the BESs research is the lack of a high-quality database that is developed through well-controlled experiments with a high-throughput data-collecting system. Here, we developed a new high-throughput potentiostat with 96 well plates with silk-screen-printed electrodes. With this potentiostat, we obtained 576 time-profiles of microbial current production for viewing the complex landscape of the parameters, namely, the redox mediator concentration and the electrode potential. This dataset contains the following materials:</p> <ul> <li>Current production profiles for <em>Shewanella </em>(Data with average of four data sets for impact of mediators.zip)</li> <li>Summary of the calculated values (statistics summary.csv)</li> <li>Python code for calculating the maximum slope (Slope EF.py)</li> <li>Python codes for Bayesian estimation (2D Bayesian Optimization mapping.py and 2D Bayesian Optimization_slice.py)</li> </ul>
Reduction of chickens use to perform in vitro pre-screening of novel anticoccidials by miniaturisation and increased throughput of the current Eimeria tenella compound-screening model
<p>In vitro models have supported important advances in biomedical sciences and have significantly contributed to reduce the use of experimental animals in different disciplines. We have developed an in vitro model for the evaluation of potential anticoccidial properties of novel compounds aimed to control chicken coccidiosis, a costly disease for the poultry industry. This disease is caused by protozoan parasites of the genus <em>Eimeria</em> (Apicomplexa), and it is mainly controlled by chemoprophylaxis with ionophors and chemical anticoccidials; however, there is an overall agreement about the limitation of these classical drugs and the need to improve current methods of control. Anticoccidial activities of novel compounds is currently evaluated by expensive experiments that involve large numbers of chickens. The use of our in vitro model for the pre-screening of essential oils led to a reduction of 67% of the chickens used in the vivo trials for validation. In this study, we describe how further optimisation of this in vitro model by miniaturisation can have an additional impact on the number of chickens used for the generation of parasite stocks for provision of the in vitro model (which cannot be done in vitro). We have estimated that the use of one chicken could support the evaluation of ten compounds with a 96-well plate format vs. only two with a 24-well plate format, which means an 80% of chicken use reduction. In this study, we have proved that the miniaturisation into a 96-well plate format has perfectly mimicked the invasion and replication observed before in the 24-well plate format. In addition, this format has allowed the simultaneous pre-screening of higher numbers of anticoccidial drugs at different concentrations following streamlined protocols in a more cost-effective way, factors that are beneficial for a wider uptake of the model by other researchers investigating anticoccidial compounds. </p>
Data from high throughput SNP-chip as cost effective new monitoring tool for assessing invasion dynamics in the comb jelly Mnemiopsis leidyi
<p class="MsoNormal"><span>High throughput low-density SNP arrays provide a cost-effective solution for population genetic studies and monitoring of genetic diversity as well as population structure commonly implemented in real time stock assessment of fish species. However, the application of high throughput SNP arrays for monitoring of invasive species has so far not been implemented. We developed a species-specific SNP array for the invasive comb jelly <em>Mnemiopsis leidyi</em> based on whole genome resequencing data. Initially, </span><span>a total of</span><span> </span><span>1,</span><span>395</span><span> </span><span>high quality </span><span>SNPs</span><span> were identified</span><span> </span><span>u</span><span>sing stri</span><span>ngent</span><span> filtering criteria</span><span>. From those, 192 assays were designed and validated, resulting in the final panel of 116 SNPs. Markers were diagnostic between the northern and southern <em>M. leidyi</em> lineages and highly polymorphic to distinguish populations. Despite using a reduced representation of the genome, our SNP panel yielded comparable results to using a whole genome resequencing approach (832,323 SNPs), recovering similar values of genetic differentiation between samples and detecting the same clustering groups when performing Structure analyses. The resource presented here provides a cost-effective, high throughput solution for population genetic studies, allowing to routinely genotype large number of individuals. Monitoring of genetic diversity and effective population size estimations in this highly invasive species will allow for the early detection of new introductions from distant source regions or hybridization events. Thereby, this SNP chip represents an important management tool in order to understand invasion dynamics and </span><span>opens the door for implementing such methods for a wider range of alien invasive species.</span></p> <div></div>
myVCF: a desktop application for high-throughput mutations data management
<p>Next-generation sequencing technologies have become the most powerful tool to discover genetic variants associated with human diseases. Although the dramatic reductions in the costs facilitate the use in the wet-lab and clinics, the huge amount of data generated renders their management by non-expert researchers and physicians extremely difficult. Therefore, there is an urgent need of novel approaches and tools aimed at getting the ‘end-users’ closer to the sequencing data, facilitating the access by non-bioinformaticians, and to speed-up the functional interpretation of genetic variants. We developed myVCF, a standalone, easy-to-use desktop application, which is based on a browser interface and is suitable for Windows, Mac and UNIX systems. myVCF is an efficient platform that is able to manage multiple sequencing projects created from VCF files within the system; stores genetic variants and samples genotypes from an annotated VCF files into a SQLite database; implements a flexible search engine for data exploration, allowing to query for chromosomal region, gene, single variant or dbSNP ID. Besides, myVCF generates a summary statistics report about mutations distribution across samples and across the genome/exome by aggregating the information within the VCF file. In summary, the myVCF platform allows end-users without strong programming and bioinformatics skills to explore, query, visualize and export mutations data in a simple and straightforward way.</p>
Dataset, Model Statistics, and 3D designs for "From Eyes to Cameras: Computer Vision for High-Throughput Liquid-Liquid Separation"
<p>Dataset, model statistics, and 3D design of high throughput platform associated with HeinSight3.0. </p> <p> </p> <p>Pre-print: https://chemrxiv.org/engage/chemrxiv/article-details/65e5481f9138d231619c1879</p> <p> </p> <p>The code and model of HeinSight3.0 can be found at (https://doi.org/10.5281/zenodo.11053915)</p>
Data for "High-Throughput Computational Evaluation of Low Symmetry Pd2L4 Cages to Aid in System Design"
<p>In the following subdirectories are the input and output of Gaussian calculations + structures from screening for this publication:</p> <p>chemrxiv: <a href="https://chemrxiv.org/engage/chemrxiv/article-details/60c758e0ee301c7eadc7b7df">10.26434/chemrxiv.14604294</a></p> <p>Published: <a href="https://onlinelibrary.wiley.com/doi/10.1002/anie.202106721">10.1002/anie.202106721</a></p> <p>Previously uploaded in 10.5281/zenodo.8432296 and <a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer">https://github.com/andrewtarzia/citable_data</a></p> <p>Software repository: <a href="https://github.com/andrewtarzia/unsymm_match">github.com/andrewtarzia/unsymm_match</a></p> <p>screening_structures directory:</p> <ul> <li>contains the structures from xTB optimisation that were used in ranking in structures.tar.gz as `.mol` files</li> <li>all_cage_results.txt contains their properties for ranking</li> </ul> <p>single_point_dft directory:</p> <ul> <li>contains the structures and output of single point DFT calculations</li> <li>during the revision process, we confirmed (based on reviewer suggestions) our DFT validation results using ORCA 4.2.1 with PBE0 and B97-3c in the gas phase. These results were consistent with our previous ones, so were not added to the manuscript. But are useful for future work! <ul> <li>These results are in the s_orca directory.</li> </ul> </li> </ul> <p>free_energy_calculations directory:</p> <ul> <li>during the revision process, it was suggested to calculate the free energies using the xTB method (low-cost) and compare that to the total energies we use.</li> <li>the script `run_gfn2_free_energy.py` in the unsymm_match code repository does this for top candidate ligands using the stko.XTB class. <ul> <li>for each structure, the free energy is output to a .fey file.</li> </ul> </li> </ul>
Dataset for interface calculations as BSON mongodump and JSON formats for the publication: "High-throughput generation of potential energy surfaces for solid interfaces"
<p>This dataset that contains the results presented in the journal article entitled "High-throughput generation of potential energy surfaces for solid interfaces" that was published in Volume 207 of the Elsevier journal Computational Materials Science.</p> <p>The dataset consists of a dump of a MongoDB database with a single collection that contains data on 6 solid interfaces including the generalized stacking fault energies, corrugation, interface distances and adhesion sites for the film and the substrate at minimum and maximum adhesion energy configurations, and images of the full potential energy surface (PES).</p> <p>The data is served in two different formats; a BSON mongodump folder that can be restored to a MongoDB instance using the mongorestore tool, and additionally as simple .json files. The contents are identical and the users are encouraged to choose the format that is convenient for them.</p>
Sample data for "Live Cell Fluorescence Microscopy – An End-to-End Workflow for High-Throughput Image and Data Analysis"
<p>This repository contains:</p> <ul> <li> <p>Sample data for the "Live Cell Fluorescence Microscopy – From Sample Preparation to Numbers and Plots" methodology paper by Zahumensky & Malinsky. The paper describes the preparation of live yeast cell samples for microscopy, the subsequent semi-automatic analysis of the microscopy images using our custom-written Fiji macros, and automatic processing of the output (Results table) from the image analys using custom-written R scripts. The data provided here are real experimental data from two publications of our group: Zahumensky et al., 2022 and Vesela et al., 2023</p> </li> <li> <p>"Results tables" from the Fiji based analysis</p> </li> <li> <p>Outputs of the processing of these Results tables using our R scripts, in the form of summary tables, graphs, and statistical analyses</p> </li> </ul>
Data from: Microfluidic Enrichment Barcoding (MEBarcoding): a new method for high throughput plant DNA barcoding
<p>DNA barcoding has become a valuable tool to support species identification with a broad range of applications in fields such as traditional taxonomy, ecology, forensics, food analysis, and environmental science. We introduce Microfluidics Enrichment Barcoding (MEBarcoding) for plant DNA Barcoding, a cost-effective method for high throughput DNA barcoding. MEBarcoding uses the Fluidigm Access Array™ to simultaneously amplify targeted regions for 48 DNA samples and hundreds of PCR primer pairs (a total of 23,040 PCR products) during a single thermal cycling protocol. A second generation instrument from Fluidigm, called the Juno™, can accommodate 192 DNA samples simultaneously. As a proof of concept, we developed a microfluidic PCR workflow using the Fluidigm Access Array™ and Illumina MiSeq to generate new sequences from 96 samples for each of the four primary DNA barcode loci in plants: rbcL, matK, trnH-psbA, and ITS (384 total sequences). This workflow was used to build a reference library that includes 78 families and 96 genera from all major plant lineages, including bryophytes, ferns and lycophytes, gymnosperms, and all major groups of angiosperms, which are currently lacking in public databases. Our results demonstrate that this technique offers a highly efficient alternative method to traditional PCR and Sanger sequencing by increasing the estimated number of plant DNA barcodes that can be sequenced by a single technician in one week by 800%, at a reduced cost, and by generating a barcode library with a more comprehensive taxonomic coverage.</p>
ZymoSoups: A high-throughput forward genetics method for rapid identification of virulence genes in Zymoseptoria tritici
<p>These data were used to generate figures and summarise the number of mutations in 18 re-sequenced genomes of <em>Zymoseptoria tritici. </em>The isolates genotyped in this VCF file are all UV-mutegenized strains of the reference isolate IPO323.</p> <p><strong>Abstract</strong></p> <p><span><span>Septoria tritici blotch is caused by the fungus </span></span><em><span><span>Zymoseptoria</span><span> tritici</span> </span></em><span><span>and</span><span> poses a major threat to wheat </span><span>productivity</span><span>. </span><span>There are over twenty mapped loci in wheat that confer strong (gene-for-gene) resistance </span><span>against this pathogen</span><span>, h</span><span>owever</span> <span>t</span><span>he corresponding genes in </span></span><em><span><span>Z. tritici</span></span></em><span><span> that confer virulence against distinct </span></span><span><span>R</span></span><span> <span>genes </span><span>remain</span> <span>largely unknown</span><span>. </span><span>In this study, we developed a</span> <span>rapid </span><span>forward genetics </span><span>methodology</span> <span>to </span><span>identify</span><span> genes that enable </span></span><em><span><span>Z. tritici</span></span></em><span><span> to gain virulence </span><span>on </span><span>previously resistant wheat varieties. </span><span>We</span><span> used the known</span><span> gene-for-gene interaction between </span></span><span><span>Stb6</span></span><span><span> and </span></span><span><span>AvrStb6</span></span><span><span> as </span><span>a </span><span>proof of concept that this method could quickly recover single candidat</span><span>e</span><span> virulence genes</span><span>. We subjected the avirulent </span></span><em><span><span>Z. tritici</span></span></em><span><span><em> </em>strain IPO323</span><span>, which carries the recogni</span><span>z</span><span>ed </span></span><span><span>AvrStb6</span></span><span><span> allele,</span><span> to UV mutagenesis</span><span> and</span><span> generat</span><span>ed</span><span> a library of over </span><span>66</span><span>,</span><span>000 </span><span>surviving spores</span><span>. </span><span>We screen</span><span>ed</span><span> these </span><span>survivors</span><span> on leaves of the resistant wheat variety Cadenza</span><span>,</span><span> in</span><span> mixtures</span> <span>(</span><span>soups</span><span>)</span><span> ranging from </span><span>100</span><span>-</span><span>500</span> <span>survivors</span><span> per soup. </span><span>We </span><span>identified</span><span> five soups</span><span> with </span><span>a </span><span>gain</span><span>-</span><span>of</span><span>-</span><span>virulence (</span><span>GoV</span><span>)</span><span> phenotype </span><span>relative</span><span> to the IPO323 parental strain</span><span> and re-sequenced 18 individual isolates, including four control isolates and two </span><span>isolates</span><span> lacking virulence</span><span>,</span><span> when screened </span><span>individually.</span> <span>Of </span><span>the </span><span>12 </span><span>confirmed </span><span>GoV</span> <span>isolates</span><span>, o</span><span>ne had a single nucleotide polymorphism (SNP) in the </span></span><span><span>AvrStb6</span></span><span><span> coding region. </span><span>T</span><span>he other 11 </span><span>GoV</span> <span>isolates</span> <span>exhibited</span> <span>large</span><span> (~70Kb)</span> <span>deletions at the end of chromosome 5, including the </span></span><span><span>AvrStb6</span></span><span><span> locus. </span><span>Our findings </span><span>demonstrate</span><span> the </span><span>efficiency </span><span>of this forward genetic approach in elucidating the genetic basis of qualitative resistance to </span></span><span><span>Z. tritici</span></span><span><span> and the </span><span>potential </span><span>to rapidly </span><span>identify</span><span> other</span><span>,</span><span> currently unknown</span><span>,</span> </span><span><span>Avr</span></span><span><span> genes in this pathogen. </span></span></p> <p><span><strong>Analysis pipeline</strong></span></p> <p><span>The pipeline used to generate this filtered vcf file and tab delimited file is publicly available at https://github.com/megancamilla/GATK4_Zymoseptoria</span></p> <p><span><strong>Isolate Data Accessibility</strong></span></p> <p><span><span>The individual fastq files for each isolate included in this study have been uploaded to NCBI's Short Read Archive (SRA), project number PRJNA1017776. This project </span><span>contains</span><span> 18 re-sequenced samples (SAMN37407989-SAMN37407972),</span> <span>which are UV mutagenized IPO323. Short Read Archive (SRA) accession numbers are SRR26072101-SRR26072118. </span> </span></p>
Do we similarly assess diversity with microscopy and High Throughput Sequencing? Case of microalgae in lakes.
<p>These are the repository files of the paper "Do we similarly assess diversity with microscopy and High Throughput Sequencing? Case of microalgae in lakes" published in Organisms Diversity and Evolution</p> <p>In these files are given:</p> <p>- the sampling sites descrptions (coordinates, lake names)</p> <p>- species relative abundances obtained with light microscopy for each sampling site</p> <p>- OTUs amounts and relative abundances obtained High-Throughput Sequencing for each sampling site</p> <p>- code correspondence between lake codes and FastQ files codes</p> <p>- FastQ files of the sampling sites</p>
Discovery of tandem and interspersed segmental duplications using high throughput sequencing
<p>We developed novel algorithms to accurately characterize tandem, direct and inverted interspersed segmental duplications using short read whole genome sequencing data sets. We integrated these methods to our TARDIS tool, which is now capable of detecting various types of SVs using multiple sequence signatures such as read pair, read depth and split read. We evaluated the prediction performance of our algorithms through several experiments using both simulated and real data sets. In the simulation experiments, using a 30x coverage TARDIS achieved 96% sensitivity with only 4% false discovery rate. For experiments that involve real data, we used two haploid genomes (CHM1 and CHM13) and one human genome (NA12878) from the Illumina Platinum Genomes set. Comparison of our results with orthogonal PacBio call sets from the same genomes revealed higher accuracy for TARDIS than state of the art methods. Furthermore, we showed a surprisingly low false discovery rate of our approach for discovery of tandem, direct and inverted interspersed segmental duplications prediction on CHM1 (less than 5\% for the top 50 predictions). </p>
Thermodynamics-driven, high-throughput analysis of protein stability with MoltenProt
<p>Data for thermal unfolding curves for various proteins.</p> <p>Measured parameters: intrinsic fluorescence (330nm, 350nm), scattering</p> <p>Files in XLSX format represent annotated output data from NanoTemper Prometheus NT.48.</p> <p> </p>
Supplementary Data for "Identifying Promising Metal−Organic Frameworks for Heterogeneous Catalysis via High-Throughput Periodic Density Functional Theory"
<p>Supplementary data to accompany:</p> <p>A.S. Rosen, J.M. Notestein, R.Q. Snurr. "Identifying Promising Metal-Organic Frameworks for Heterogeneous Catalysis via High-Throughput Periodic Density Functional Theory", J. Comput. Chem (2019). DOI: 10.1002/jcc.25787</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.