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1,661 results for “throughput”
Working time, energy throughput and value added embodied in production, consumption and trade by subsectors for the US, the EU, China and rest of the world (2011)
<p>This repository contains the data needed to reproduce the results in:</p> <p>Pérez-Sánchez, L., Velasco-Fernández, R., Giampietro, M., The international division of labor and embodied working time in trade for the US, the EU and China, Ecological Economics. <a href="http://doi.org/10.1016/j.ecolecon.2020.106909">https://doi.org/10.1016/j.ecolecon.2020.1069097</a></p> <p>Sources of data are specified in the dataset (under tab "references")</p> <p> </p>
Statistical analysis and dataset for: A high-throughput and sensitive method for food preference assays in walking insects
<p>Linked to the journal article published in bioRxiv (https://doi.org/10.1101/2024.04.10.588882).</p> <p><em><strong>Abstract</strong></em></p> <p>Insects pose significant challenges in both pest management and ecological conservation. Often, the most effective strategy is employing toxicant-laced baits, which must also be designed to specifically attract and be preferred by the targeted species for optimal species-specific effectiveness. However, traditional methods for measuring bait preference are either non-comparative, meaning that most animals only ever taste one bait, or suffer from methodological or conceptual limitations. Here we demonstrate the value of direct comparison food preference assays using the invasive and pest ant <em>Linepithema humile </em>as a model. We compare the food preference sensitivity of non-comparative (one visit to a food source) and sequential comparative (visiting one type of food then another) assays at detecting low levels of aversive quinine in sucrose solution. We then introduce and test a novel dual-choice feeder method for simultaneous comparative evaluation of bait preferences, testing its effectiveness in discerning between foods with varying quinine or sucrose levels. While the non-sequential assay could not detect aversion to 1.25mM quinine in 1M sucrose, the sequential comparative approach detected aversion to quinine levels as low as 0.94mM. The novel dual feeder method approach could detect aversion to quinine levels as low as 0.31mM, and also preference for 1M sucrose over 0.75M sucrose. The dual-feeder method, combines the sensitivity of comparative evaluation with high throughput, ease of use, and avoidance of interpretational issues. This innovative approach offers a promising tool for rapid and effective testing of bait solutions, contributing to the development of targeted control strategies. Moreover, the method can be easily modified for application to a wide range of walking insects, such as cockroaches, crickets, and beetles.</p>
Dataset of the paper entitled methods for high-throughput screening of novel agents against the maize pest, Diabrotica virgifera virgifera (Coleoptera: Chrysomelidae)
<p>Title: Methods for high-throughput screening of novel agents against the maize pest, Diabrotica virgifera virgifera (Coleoptera: Chrysomelidae) </p> <p>Authors: Sri Ita Tarigan, Gyorgy Turoczi, Jozsef Kiss, Stefan Toepfer</p> <p>Abstract: <br>The western corn rootworm, <em>Diabrotica virgifera virgifera</em> (Coleoptera: Chrysomelidae), poses a significant threat to maize crops in North America and Europe, necessitating development of novel, effective, and less disruptive crop protection agents. With recent bans on key insecticides and concerns about overuse of remaining options, there is an urgent need for accessible and comparable screening methods. We propose comparative high-throughput screening methods against the eggs, larvae and adults of this pest, emphasizing the importance of suitable positive controls tailored to the specific bioassay types. We evaluated seven common insecticides (imidacloprid, clothianidin, acetamiprid, novaluron, cypermethrin, chlorpyrifos-methyl, spinosad) against eggs, larvae, and adults as potential positive controls for each of the proposed assay methods. Dipping assays with ready-to-hatch eggs revealed several ingredients to cause mortality; but imidacloprid might be most suitable as a positive control due to its robust dose-response in reducing egg hatching and causing mortality of hatching neonates. Larval bioassays using artificial diet overlay assays revealed mortality caused by all insecticides, with imidacloprid and acetamiprid exhibiting best dose-mortality response curves as well as sublethal effects. Adult bioassays using artificial diet-core overlay assays revealed mortality caused by all insecticides, with cypermethrin or acetamiprid exhibiting best dose-mortality response curves. The provided ED <sub>50</sub>, ED <sub>80</sub> values, and dose-response equations offer valuable insight for researchers in selecting appropriate positive controls for screening new crop protection agents or assessing resistance levels against different life stages of this pest.</p> <p>Data:</p> <p>The data file is related to the screening of commercial insecticides against eggs, first instar larvae (L1) and adults of the maize pest, <em>Diabrotica virgifera virgifera</em> using standard bioassays. We are proposing comparative high-throughput screening methods against the eggs, larvae and adults of this maize pest. This includes the crucial aspect of suitable positive controls tailored to the specific bioassay type. We evaluated seven common insecticides (imidacloprid, clothianidin, acetamiprid, novaluron, cypermethrin, chlorpyrifos-methyl, spinosad) against eggs, larvae, and adults as potential positive controls for each of the proposed assay method. To access effects and dose-responses of commonly used insecticides on eggs, we applied standard screening methods under controlled semi-sterile conditions.</p> <p>For egg bioassays, eggs were transferred to the 200 ml of treatments in the eppendorf tubes and then soaked for 1 hour. Then 20µl with 10 to 20 eggs were pipetted onto a filter paper in a petri dish (150 mm×25 mm). Then 100 µl of sterilized tap water was added for moisture. The pipette tip was replaced between treatments. The eggs been transferred were counted per filter paper and dish (15± 8). The eggs were then incubated in the dishes at 23-25<sup>0</sup>C for 7 days, when the experiment was terminated. Egg hatching, mortality of newly hatching larvae, and days until start of egg hatching were observed under stereo microscope and recorded. Data were collected at 1,3, 5 and 7 days after treatments.</p> <p>To assess the effect and dose-responses of commonly used insecticides on neonates of <em>D. v. virgifera</em>, we applied artificial diet-overlay bioassays under controlled semi-sterile conditions. Each insecticide was prepared in at least six concentrations. Each bioassay consisted of 3 to 6 polystyrene plates of 96 wells each (07-6096 of Biologix Ltd., USA, or Costar 3917 of Corning Inc., USA). Each well had a volume of 330 µl, with a diameter of 5 mm, a height of 10 mm, and a surface area of 0.34 cm². 190 µl of the diet were pipetted into each 330 µl well, filling each to approximately 2/3<sup>rd </sup>of its capacity. Plates containing the diet were left to dry in a laminar flow cabinet for 45 minutes and then stored overnight at temperatures ranging from 3 to 5°C. The following day, treatments were applied. This is, 17 µl of a treatment was applied to the 0.34 cm<sup>2</sup> diet surface reaching good coverage and therefore forcing the after-placed larvae to feed through (10 to 100 µl pipette Biohit TM Proline). Each treatment was applied to 8 wells per plate. Following application, the plates were allowed to dry for a duration of 1 to 1.5 hours and were subsequently cooled for 1 hour in a refrigerator set at temperatures between 23 to 25°C. Each well received one neonate larva, carefully placed on the diet surface using a fine artist brush. A vigorous and visibly healthy larva was selected, lifted from the end of the abdomen with the brush, maneuvered towards a well surface, and allowed to crawl off the brush onto the diet. To avoid systematic errors, larvae were not arranged in treatment column order but rather in a rectangular pattern. After every 12 individual larvae, the brush was cleaned using 70% ethanol followed by sterile tap water. The filled plate was sealed with an optically clear adhesive qPCR seal sheet (#AB-1170, Termo Scientific, USA, or #BS3017000, Bioleader, USA), enabling data assessments without the need to open the plate. Four to five holes were carefully made with fine 00-insect pins into the seal per well to facilitate aeration. The plates, housing the larvae, were then incubated in a dark, ventilated incubator at a temperature of 23-25 °C and a relative humidity of 50 to 90% for a period of 5 days. We assessed mortality and stunting larvae within 3 and 5 days. </p> <p>To access the effect and dose-responses of common insecticides on <em>D.v.virgifera</em> adults, artificial diet-overlay bioassays with different doses were performed under controlled, semi-sterile conditions. Each insecticide was prepared in at least six concentrations. Active ingredients as specified on the product labels underwent serial dilutions using sterile tap water. Sterilized tap water was used as untreated control. In detail, each bioassay consisted of 6 polystyrene plates of 6 wells each (Eppendorf® 0030720016). Each treatment was applied to 3 wells of each plate per bioassay. The adult diet for a bioassay had been prepared 1-7days before treatment and adult infestation. The diet was prepared under semi-sterile conditions. The diet was poured out to 5-6 sterile 11 mm Petri dishes. The plates with diet were allowed to dry for up to 15 minutes under laminar flow cabinet then stored at 3 to 5°C overnight.The following day, a core of the diet was initially transferred to each well using flamed iron core-cutter (1 cm diameter) under a laminar flow. A core diet was placed each of the 6 wells of the plates. Approximately 40 µl of the treatments were then applied across the surface of diet core (0.34 cm<sup>3</sup>). The following day, a core of the diet was initially transferred to each well using flamed iron core-cutter (1 cm diameter) under a laminar flow. A core diet was placed each of the 6 wells of the plates. Approximately 40 µl of the treatments were then applied across the surface of diet core (0.34 cm<sup>3</sup>). Adult were subsequently transferred from the rearing cage into the wells of the 6-well plates containing the diet and treatments using a tube aspirator. For ease of transfer, the adults were cooled in a fridge for 4 to 7 minutes. Each well plate received 3 to 4 adults. Plates were sealed and incubated at 23-25<sup>0</sup>C, 50–90% r.h, L: D 12:12. Adult mortality were recorded on days 1,3, 5, 7 of experiment. </p> <p>To allow comparisons between experiments, data were standardized to the data of the corresponding negative control, usually sterilized tap water, as follows: standardized data = 100 × (data in negative control - data in treatment)/maximum (data in control or in treatment). The distributions of the data were investigated using histograms and QQ normal and detrended normal probability. Skewness and kurtosis of residuals was also observed for normality of influences of treatments on eggs, neonates, or adults. Equality of variances was assessed using Levene’s test. Multiple comparisons were performed using the Tukey HSD post hoc test for data with equal variances and the Games-Howell post hoc test for data with unequal variances. For each tested insecticide, linear and logarithmic regression models were fit to the dose-response data. In case of significant linear or logartimic relathionships, doses leading to 50% or 80% of relative effects (ED <sub>50,80</sub>) were calculated. </p> <p>The raw data as well as the standardised data are available as a csv file on zenodo. </p> <p> </p> <p> </p>
Quantification of Giant Unilamellar Vesicle Fusion Products by High-Throughput Image Analysis - Imaging Flow Citometry Data
<p>Imaging flow citometry (IFC) datasets analysed in "Quantification of Giant Unilamellar Vesicle Fusion Products by High-Throughput Image Analysis" (under revision).</p> <p>The folders contain acquisitions of giant unilamellar vesicles (GUVs) for lipid exchange and content exchange controls, with file naming convention DATE_SAMPLE_REPLICATE.rif, content exchange is indicated by CE samples in the 20230228_CE.zip folder, lipid exchange by LE samples in the 20221222_LE.zip folder. 24 samples per set are included, triplicates of isolated P1 (DOPE Af488 0.6% in LE; Dex-Af488 40 uM for CE), P2 (DOPE Cy50.6% in LE; Dex-Af647 10 uM for CE), NC (P1 + P2 1:1), PC (DOPE Af488 0.3% + DOPE Cy5 0.3 in LE; Dex-Af488 20 uM + Dex-Af647 5 uM for CE), and M samples numbered 1 to 4, prepared by mixing P1, P2 and PC in different ratios (M1= 1:1:1; M2= 1:1:0.5; M3= 1:1:0.1; M4= 1:1:0.05).</p> <p>Only .rif files are provided, they have to be elaborated via compensation and application of an analysis template using the Amnis IDEAS software. Compensation matrices for lipid exchange (20230217_LEcom.ctm) and content exchange (20230217_CEcomp.ctm) are included, as well as the analysis template (Lipid_exchange_analysis_6.2.ast). Gating in the latter may have to be adjusted to analyse LE and CE experiments.</p> <p>10000 objects in the GUV population or 50000 objects in total were acquired in each file. The files were elaborated in batch mode, outputting the statistic reports (Statistics report CE.txt for CE; Statistics report LE.txt for LE) that were elaborated using an R scirpt (included, IFC_analysis.R) </p>
Raw dataset for: High-throughput multimodal wide-field Fourier-transform Raman microscope
<p>This is the Raw spectral dataset of the data published in 10.1364/OPTICA.488860</p> <p>Data are arranged as follows:</p> <p>wavenumber [Nx1]</p> <p>Hyperspectrum_cube [Nx2, A, B]: hyperspectral datacube, where: Hyperspectrum_cube (1:N, :, :) is the real part; Hyperspectrum_cube (N+1:2N, :, :) is the imaginary part</p> <p>maximum [1x1]</p> <p>minimum [1x1].</p> <p>N: number of spectral bands</p> <p>A and B: size of the spatial coordinates</p> <p>Spectral amplitudes are obtained by: Hyperspectrum_cube=double(Hyperspectrum_cube)./(2.^16-1).*maximum+minimum</p>
High-Throughput Density Functional Theory Screening of Double Transition Metal MXene Precursors
<p>This dataset contains density functional theory results on a set of double-transition metal MXene precursors</p>
Artificial Intelligence for EU Decision-Making: Effects on Citizens Perceptions of Input, Throughput and Output Legitimacy
<p>The uploaded dataset was used for the statistical analysis of the pre-print "Artificial Intelligence for EU Decision-Making: Effects on Citizens’ Perceptions of Input, Throughput and Output Legitimacy" (Permanent identifier: <a href="https://arxiv.org/abs/2003.11320">arXiv:2003.11320</a>)</p> <p>A lack of political legitimacy undermines the ability of the European Union (EU) to resolve major crises and threatens the stability of the system as a whole. By integrating digital data into political processes, the EU seeks to base decision-making increasingly on sound empirical evidence. In particular, artificial intelligence (AI) systems have the potential to increase political legitimacy by identifying pressing societal issues, forecasting potential policy outcomes, informing the policy process, and evaluating policy effectiveness. This paper investigates how citizens’ perceptions of EU input, throughput, and output legitimacy are influenced by three distinct decision-making arrangements: (1) independent human decision-making (HDM); (2) independent algorithmic decision-making (ADM) by AI-based systems; and (3) hybrid decision-making by EU politicians and AI-based systems together. The results of a pre-registered online experiment (n = 572) suggest that existing EU decision-making arrangements are still perceived as the most democratic (input legitimacy). However, regarding the decision-making process itself (throughput legitimacy) and its policy outcomes (output legitimacy), no difference was observed between the status quo and hybrid decision-making involving both ADM and democratically elected EU institutions. Where ADM systems are the sole decision-maker, respondents tend to perceive these as illegitimate. The paper discusses the implications of these findings for (a) EU legitimacy and (b) data-driven policy-making.</p>
Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection
<p>Processed TCRbeta and TCRalpha repertoires after mild COVID-19 (Version 2.0: day 85 timepoints added) infection, see preprint: <a href="https://www.biorxiv.org/content/10.1101/2020.05.18.100545v3">https://www.biorxiv.org/content/10.1101/2020.05.18.100545v3</a></p> <p>and GitHub repository: <a href="https://github.com/pogorely/Minervina_COVID">https://github.com/pogorely/Minervina_COVID</a></p> <p>Two donors (M and W), two biological replicates of PBMC (F1 and F2), CD4+, CD8+, and Memory subpopulations for each post-infection time points (day 15, 30, 37, 45, 85 post-infection), and pre-infection PBMC repertoires sampled in 2019 and 2018. </p>
Flow diagram for analysis of high-throughput sequencing data
<p>Tex code and resulting pdf image, summarising the data processing pipeline of high-throughput sequencing data (fastq format files), through mapping the data to a reference genome, and then discovery and genotyping of sequence variants. The latter stage uses both 'GATK Haplotype Caller' for smaller variants, such as single-nucleotide polymorphisms and insertion-deletion polymorphisms, and Genomestrip for variants such as deletions and duplications greater than 1000 nucelotide bases in length. Note that the flow diagram is intended to represent what steps were take in the study, and does not necessarily represent the current optimum methods.</p> <p>The manuscript for which this image is a part of can be found open-access at F1000 Research "Whole genome resequencing of a laboratory-adapted <em>Drosophila melanogaster </em>population sample" https://f1000research.com/articles/5-2644/v1 doi: 10.12688/f1000research.9912.1</p> <p> </p>
A high-throughput 3D X-ray histology facility for biomedical research and preclinical applications - Supplementary Data
<p><strong>Videos</strong></p><ul><li><strong>Video 1</strong> A video going through the Z stack in single slices. This is a cross- sectional view of the XRH image stack along the XY plane. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 2 </strong>A video going through the Y stack in single slices. This is a cross- sectional view of the XRH image stack along the XZ plane. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 3 </strong>A video going through the X stack in single slices. This is a cross- sectional view of the XRH image stack along the YZ plane. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 4 </strong>3D X-ray histology (XRH) is a µCT -based workflow tailored to fit seamlessly into current histology workflows in biomedical and pre-clinical research, as well as clinical histopathology. Microanatomical detail can be captured from standard (non-stained) formalin-fixed and paraffin-embedded (FFPE) tissue blocks.</li><li><strong>Video 5</strong> Average Intensity Projection (AIP) of the sample through the Histologically relevant plane. This is a 2D visualisation rendering the Average Intensity of 20x single XY slices along the z-axis of the stack. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 6 </strong>Maximum Intensity Projection (MIP) of the sample through the Histologically relevant plane. This is a 2D visualisation rendering the Maximum Intensity of 20x single XY slices along the z-axis of the stack. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 7 </strong>Standard deviation projection of the sample going through the histologically relevant plane. This is a 2D visualisation rendering the Standard Deviation of 20x single XY slices along the z- axis of the stack. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li></ul><p><i>* <strong>Videos 5 -7</strong> are also referred to as "thick-slice rolls" </i>- <i>Thick-slice rolling is a 2D thick-slice viewing that allows rolling of a pre-selected number of slices (n) along the z-axis of the 3D data. A single thick-slice roll forwards is accomplished by translating the thick-slice by one single slice forwards; that is moving forward by one (+1) slice from the first and nth element and reapplying the criteria or operations to the new slice sub-stack.</i><br> </p><p><strong>The questionnaire used to collect feedback about the needs of the XRH community.</strong></p><ul><li>Survey.docx</li><li>Survey.pdf</li></ul><p><br><strong>Exemplar report of a semi-automatically generated augmented PDF file</strong> that contain sample information, imaging settings, still images with descriptive figure legends, and links to corresponding online videos</p><ul><li>DEMO02019-FFPE_report_99EbPXG.pdf</li></ul><p> </p><p>= = = = = = = = = = = = = = = = <br><strong>System performance data ZIP</strong><br>= = = = = = = = = = = = = = = = </p><p>This ZIP file contains imaging data collected through different systems and setups at the XRH facility at the μ-VIS X-ray Imaging Centre at the University of Southampton for the purpose of acceptance and/or system performance characterisation. Below is an overview of the folder structure and its contents</p><p>The following files are X-ray imaging data collected on September 28, 2017, using the Med-X system and a Jima phantom at 55 kV peak and 7 Watts. </p><ul><li>20170928_MEDX_1642_JIMA_55kVp7W-2.tif</li><li>20170928_MEDX_1642_JIMA_55kVp7W.tif</li><li>20170928_MEDX_1642_JIMA_55kVp7W.tif.profile.xml</li></ul><p>This PDF document is related to a QRM MicroCT bar pattern phantom, and its specifications</p><ul><li>QRM-MicroCT-Barpattern-Phantom.pdf</li></ul><p>Graphs showing the calculated focal-spot size as a function of the X-ray power (W) for the Molybdenum rotating target calculated using Edge Modulation function testing. The performance is then compared with the performance of the Reflection target across the same range of powers. Raw data can be found in XRH_QRM_Refl-vs-Rot-TargetComparison_SingleReconSlices_5umPixelSize folder. Test performed in July 2021. </p><ul><li>XRH_202107_MoRot-testing_EdgeModFunction-QRMrecons+RotReflCompar.png</li></ul><p> </p><p><i><strong>/ XRH-XT-H-225-ST_FocalSpots</strong></i><br>This directory contains radiographic data collected using the XRH system with a JIMA phantom and MoRt (Molybdenum rotating), TT (Transmission), and Reflection targets.</p><ul><li>20200113_XRH_Jima test MoRT 55kV 15W.tif, 20200113_XRH_Jima test MoRT 55kV 30W.tif, etc.: <br>These files represent radiographs taken on January 13, 2020, using the XRH system, Jima phantom, MoRT target at 55 kVp and varying wattages.</li><li>20200207_XRH_JIMA 80kV TT1a.tif, 20200207_XRH_JIMA 80kV TT1b.tif, etc.<br>Similar to the above, these files are from February 7, 2020, and use 80 kVp with a TT target.</li><li>20231115_XRH_reflW_80kVp6W.tif, 20231115_XRH_reflW_80kVp6W_02.tif, etc.<br>These files are from November 15, 2023, and collected using the XRH system with a Reflection target at 80 kVp and 6 Watts.</li></ul><p><i><strong>/ XRH_QRM_Refl-vs-Rot-TargetComparison_SingleRadioFromCTs_5umPixelSize</strong></i><br>This directory contains single radiographs taken with a pixel size of 5 micrometers using the Molybdenum rotating (MoRt), and the Reflection target using tungsten (W) and Molybdenum (Mo) metals.</p><p><i><strong>/ XRH_QRM_Refl-vs-Rot-TargetComparison_SingleReconSlices_5umPixelSize</strong></i><br>This directory contains sinlge reconstruction slices of the setups mentioned above. Slices are exported from CT volumes and were used for the Edge Modulation function study. </p><p>For interpretation of the filenames in the folders listed above please see below and refer to specific files and folders for detailed information and results related to each imaging session:</p><ul><li><i><xx>kVp or <xx>kV </i>:Imaging at a peak voltage of <xx> kVp.</li><li><i><y>W</i> :Imaging at <y> Watts;<i> </i>"." is represented with "-"; i.e. 20210705_XRH_2766_PJB_TEST03552-EQPMT_W_6-9W is acquired using a power of 6.9 W</li><li><i>MoRt, TT, Refl </i> :Molybdenum, Transmission, and Reflection targets, respectively.</li><li><i>_W_ and _Mo_ </i> :Tungsten and Molybdenum target materials.</li><li><i>_horiz</i> :Reconstruction slices in line with the X-ray beam's propagation direction.</li><li><i>_vert</i> :Reconstruction slices normal to the X-ray beam's propagation direction and parallel to the detector plane.</li></ul>
Data supporting for: A High-Throughput Framework for Lattice Dynamics
<p><span>We develop an automated high-throughput workflow for calculating lattice dynamical properties </span><span>from first principles including those dictated by anharmonicity. The pipeline automatically calculates </span><span>interatomic force constants (IFC) up to 4th order from perturbed training supercells, and uses the </span><span>IFC to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free </span><span>energy and entropy. It performs phonon renormalization for dynamically unstable compounds to</span><br><span>obtain real effective phonon spectra at finite temperatures and calculates the associated free energy </span><span>corrections.</span> <span>The choice of methods and parameter selection process are done in a manner that </span><span>strikes a balance of computational efficiency and accuracy of results (as assessed through convergence </span><span>testing and comparison to experimental measurements). </span></p> <p><span>The following data includes:</span></p> <ul> <li><span>materials we calculated lattice thermal conductivities (kappa folder)</span></li> <li><span>materials we applied renormalization to get corrected free energies (renormalization folder)</span></li> </ul> <p><span>The target of this dataset is giving users a reference for our inputs and outputs when they want to run our workflow by their own.</span></p>
High-throughput robotic titration using computer vision
<ul> <li> <p>An automated HTE robotic titration using a liquid-handling robot Opentrons(OT-2) and a standard webcam enables in-situ, affordable titration analyses.</p> </li> <li>Its modular design allows adaptability for materials chemsitry and integration into automated workflows, enhancing efficiency in chemical search.</li> </ul>
2021 5Genesis Berlin Platform Field Trial RTT and Throughput Measurements
<p>RTT and Throughput measurements from the various measurement endpoints of the 2021 5GENESIS Berlin Platform Field Trials at IHP, in Frankfurt (Oder).</p>
Image dataset for the evaluation of a low-cost high-throughput plant phenotyping system
<p>This dataset contains the raw and processed images from a low-cost high-throughput plant phenotyping (HTP) system, as well as the raw and processed images that were manually acquired for comparison. The HTP images were automatically and wirelessly acquired for entire benches of plants with a system composed of a Raspberry Pi and eight GoPro cameras. The entire file system of each GoPro camera was copied directly into a subfolder of finalGoProImages (numbered by camera). The raw HTP images were processed by correcting for lens distortion, computing the "greenness index" for each individual pixel, and filtering out extreme high and low values. These processed HTP images were then saved in the "greenness" subfolder of finalGoProImages. The manually acquired images in the finalDSLR folder each represent an individual plant from one of five time points during the same greenhouse experiment. The raw manually acquired images were processed in the same manner as the raw HTP images by computing the greenness index for each individual pixel and filtering out extreme high and low values. The two tab-delimited text files include the number of green pixels and mean greenness index for each HTP (greennessGoProTable2.txt) and manually acquired (greennessDSLRTable2.txt) image.</p>
Analysis scripts for the evaluation of a low-cost high-throughput plant phenotyping system
<p>Data analyses to complement "Image dataset for the evaluation of a low-cost high-throughput plant phenotyping system" (DOI: 10.5281/zenodo.5725224). "README_SetupAndAnalyses.pdf" contains instructions for setting up the high-throughput phenotyping (HTP) system and analyzing the resulting image datasets. The analyses are split into two parts. First, the automatically acquired HTP and manually acquired (DSLR) images are processed using the Python script labeled "finalGreennessAnalyses.py". The csv file labeled "labelTable.csv" is used to rename the DSLR images in terms of the date acquired and experimental conditions and must be included for the Python script to process the DSLR images. The output of the Python script includes "greennessGoProTable.txt" containing tab-delimited data regarding foliar size and greenness for each HTP image and "greennessDSLRTable.txt" containing tab-delimited data regarding foliar size and greenness for each DSLR image. The second step of the analyses includes inferential statistics (e.g., correlations and linear mixed effects modeling) and is based on the R script labeled "ghGoProAndDSLR_toPublish2.R". The csv file labeled "parAllBenches.csv" includes average solar daily light integral (solar DLI) data that were used as part of the linear mixed effects models in R.</p>
Data for "Highly-Automated, High-Throughput Replication of Yeast-based Logic Circuit Design Assessments"
<p>Flow Cytometry and plate reader data from "High Throughput Experimentation to replicate Yeast Gates Experiment," accompanied with jupyter noteboooks to replicate the analyses. Sequencing data is <a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA784977">available separately</a>.</p> <p>Files named <code>flow_cytometrya<em>x</em></code> should be concatenated: they are individual slices of a gzipped tar file. Concatenate them and then extract with <code>tar xzf <em>filename</em></code>.</p> <p>The paper is available on <a href="https://biorxiv.org/cgi/content/short/2022.05.31.493627">Biorxiv</a>.</p> <p>The Jupyter notebooks used to analyze this data for the paper are <a href="https://github.com/rpgoldman/replication-paper-data-analysis">available on GitHub</a>.</p>
Development of ferret immune repertoire reference resources and single-cell-based high- throughput profiling assays
<p>We performed long read transcriptome sequencing of ferret splenocyte and lymph node samples full-length, non-chimeric circular consensus sequencing (CCS) reads to obtain over 120,000 high-quality immunoglobin (Ig) and T cell receptor (TCR) transcripts.</p>
Advancing Vanadium Redox Flow Battery Analysis: A Deep Learning Framework for High-Throughput 3D Visualization and Bubble Quantification via Synchrotron X-ray Tomography
<p>Dataset and model of UTILE-Redox - Deep Learning based Tool for Autonomous 3D Bubble Analysis of Vanadium Flow Batteries from Synchrotron X-ray Imaging. This project focuses on the deep learning-based automatic analysis of Vanadium Redox Flow Batteries (VRFB) Synchrotron X-ray tomographies. This repository contains the Python implementation of the UTILE-Redox software for automatic volume analysis, feature extraction, and visualization of the results.</p>
Dataset of image processing - High-throughput characterization of cortical microtubule arrays response to anisotropic tensile stress
<p>The data set contains the analysis data files from the image analysis workflow developed to quantify cortical microtubules rearrangements in the case of tensile stress (<a href="https://github.com/VergerLab/MT_Angle2Ablation_Workflow">https://github.com/VergerLab/MT_Angle2Ablation_Workflow</a>), generated form a specific dataset (https://doi.org/10.5878/17te-jg54). The files include the intermediary images processed at each step of the image analysis workflow in imageJ, the log files produced by the imageJ macro describing the input and the output images and the text files containing the quantified values. </p>
fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions - supplementary data.
<p><b>fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions - supplementary data.</b></p><p>Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.</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.