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1,661 results for “Throughput”
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 8)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 3)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 16)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 5)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 18)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 15)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 11)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Antagonism, Antagonsim Assay (Part 22)
<p>Fluorescent and darkfield images for the antagonism assay droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Synergism, Tobramycin (Part 1)
<p>Fluorescent and darkfield images for the synergism tobramycin (single antibiotic) droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 4, Synergism, Vancomycin (Part 1)
<p>Fluorescent and darkfield images for the synergism vancomycin (single antibiotic) droplets of Figure 4 of "High-throughput combinatorial droplet generation by sequential spraying." Accompanying code is found at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Fig 2, Alexa Fluor 594
<p>Images for figure 2 for Alexa Fluor portion of of "High-throughput combinatorial droplet generation by sequential spraying," with accomanying code at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
High-throughput combinatorial droplet generation by sequential spraying: Figure 3
<p>Data for Figure 3 of "High-throughput combinatorial droplet generation by sequential spraying. " Includes .tif images - accompanying MATLAB script is on GitHub at https://github.com/RenaFukuda99/High-throughput-combinatorial-droplet-generation-by-sequential-spraying. </p>
Flow Cytometry Data from "Bacterial cell surface characterization by phage display coupled to high-throughput sequencing"
<p>This record contains the flow cytometry data from the manuscript "Bacterial cell surface characterization by phage display coupled to high-throughput sequencing."</p> <p>Files are in <a href="https://docs.flowjo.com/flowjo/advanced-features/fj-acs/">Archive Cytometry Standard (ACS) format</a> . Each <code>.acs</code> file is a zip container which holds both the raw <code>.fcs</code> files and a FlowJo workspace (<code>.wsp</code>) file.</p> <p>Keywords in the workspace file identify which primary antibody (<code>primary</code>) was used and which cell genotype (<code>strain</code>) was used for each sample. The workspace also encodes the gating scheme and compensation matrix applied to each sample. Plots in the manuscript are exported from Layout views in the workspace.</p>
"Toy Data Set" referenced in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (https://doi.org/10.1101/2024.08.22.609110)
<p>This data set, referenced as "toy data set" in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (<a href="Lint-to-article">https://doi.org/10.1101/2024.08.22.609110</a>), mimics a high-throughput screening data set. To demonstrate the application of our analysis framework described in the main article this toy data set was generated. It contains in total 1536000 individual transient signals, splitted in 5 batches of each 200 plates in 1536-well plate format. Five distinct signal classes were used to resemble typical shapes encountered in biological experiments. Fequency of occurrences for each class is reported in the main article.</p>
Impact of Interval Censoring on Data Accuracy and Machine Learning Performance in Biological High-Throughput Screening
<div> <h2>Overview</h2> <div>Data and Results used in the publication entitled "Impact of Interval Censoring on Data Accuracy and Machine Learning Performance in Biological High-Throughput Screening"</div> </div> <div> <h3><strong>Data</strong></h3> <div>This folder contains the raw data used during this work.</div> <div>`EvoEF.csv` contains information on the library used (sequences, number of mutations, etc.) and the fitness (energy) used as continuous mean values. `mut.csv` contains the information about the combinatorial scaling (N vs N_norm), the number of mutations (m) and the probability of each variant using different distributions (uniform and binomial) at different $p_{WT}$.</div> <div>For further details on how the fitness values were calculated and how the combinatorial scale works, please refer to our prevoius [Paper](https://arxiv.org/abs/2405.05167).</div> <div> </div> <h3><strong>Results</strong></h3> <div> <div>This folder contains the results (outputs) of all scripts used. Such results are included in the form of `.npy` and `.npz` files. To load such files with numpy you should include the option `allow_pickle=True`.</div> </div> </div>
High-throughput behavioural phenotyping of 25 C. elegans disease models including patient-specific mutations
<p>This repository contains: all code, phenomic data, extracted features, calculated stats, normalised z-scores and timerseries data for all of the disease mutant phenologs and data in our paper: High-throughput behavioural phenotyping of 25 C. elegans disease models including patient-specific mutations.</p>
High-throughput robotic determination of hydrogen peroxide using computer vision
<p>A fully automated process of high-throughput determination of hydrogen peroxide integrating a liquid handling robot (Opentrons, OT-2) with a webcam based on chemical titration.</p>
Supplementary materials for "High-Throughput Discovery of Substrate Peptide Sequences for E3 Ubiquitin Ligases Using a cDNA Display Method."
<p>The next-generation sequencing (NGS) data of the 5th rounds' samples for LX9 library and p53deg library. The csv files contain DNA sequences read out, amino acid sequences and their read counts in descending order. </p>
High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds
<h3><em><strong>Content</strong></em></h3> <p>Dataset of the study: "High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds.</p>
Description of metabolic differences between castrated males and intact gilts obtained from high-throughput metabolomics of porcine plasma
<h3>Content</h3> <div> <p>Dataset of the study: Description of metabolic differences between castrated males and intact gilts obtained from high-throughput metabolomics of porcine plasma.</p> <p> </p> </div>
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.