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7,515 results for “screenings”

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zenodo40/100

Data for Project 'Diagnostic Accuracy, Reliability, and Construct Validity of the German Quick Mild Cognitive Impairment Screen'

Data for Project 'Diagnostic Accuracy, Reliability, and Construct Validity of the German Quick Mild Cognitive Impairment Screen' consisting of (1) the complete data set of all data analyzed for the project 'Diagnostic Accuracy, Reliability, and Construct Validity of the German Quick Mild Cognitive Impairment Screen' ('Data_Brain-IT-Validation-Qmci_for-publication.xlsx'; and (2) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.

opencc-by-4.0Nov 2023View details →

zenodo40/100

Metabolomics Peak Tables of the publication "Screening of leaf extraction and storage conditions for eco-metabolomics studies"

This dataset is a metabolomics study of maize extracts. The dataset consists of peak tables (.csv files) and MS/MS fragment patterns (.mgf files) both exported from MetaboScape. Additionally the results of a Principal Component Analysis are provided for the LLE optimisation part of the dataset. All further details are available in the publication in Plant Direct: https://doi.org/10.1002/pld3.578

opencc-by-4.0Nov 2023View details →

zenodo40/100

Measured and analyzed raw data for publication "Nanoscale spin ordering and spin screening effects in tunnel ferromagnetic Josephson junctions" (doi: https://doi.org/10.1038/s43246-024-00497-1)

The data provided by this dataset are the raw data published in the paper "Nanoscale spin ordering and spin screening effects in tunnel ferromagnetic Josephson junctions" (doi: https://www.nature.com/articles/s43246-024-00497-1).  It can be found: -In the folder figure2_IV, the current-voltage characteristics (IV) of standard Superconductor-Insulator-Superconductor Josephson Junctions (SIS JJ) and of Superconductor-Insulator-Ferromagnet-thin superconductor- Superconductor Josephson Junctions (SIsFS JJ) at 10 mK  -In the folder figure2_IVH, the magnetic dependence of the critical current of the SIsS and SIsFS at 10 mK -In the folder figure3_IVHT, the magnetic dependence of the critical current of the SIsFS as a function of the temperature T -In the figure4_gamma, the experimental and theoretical dependence of  \gamma, i.e., the magnetic moment of the S-layers normalized to the F-layer in absolute value, as a function of the characteristic energy of the inverse proximity effect

opencc-by-4.0Nov 2024View details →

zenodo40/100

Dataset: A Labeled Dataset for Osteoporosis Screening Based on Electromagnetic Attenuation

README Dataset name: osseus_dataset.csv  Version: 1.0  Dataset period: 07/01/2021 - 09/31/2023 Dataset Characteristics: Multivalued  Number of Instances: 669 Number of Attributes: 31 Missing Values: yes Area(s): Health and technology  Sources:  <ul> <li> Electronic Patient Record (EPR) - University Hospital Onofre Lopes of Federal University of Rio Grande do Norte (HUOL/UFRN), Brazil; </li> <li> OSSEUS (Osteoporosis screening based on electromagnetic waves); and, </li> <li> DXA (Dual-energy x-ray absorptiometry).  </li> </ul>   Description: The dataset “osseus_dataset.csv” (Table 1) contains elementary data related to risk factors and examinations performed by individuals in Rio Grande do Norte, Brazil, to investigate bone mineral density. Data were collected using the EPR of HUOL/UFRN, DXA, and OSSEUS, a low-cost device based on electromagnetic waves, which measures the attenuation of the signal when crossing the medial phalanx of the middle finger (PINHEIRO et al., 2021, ALBUQUERQUE et al., 2022). Descrição: O conjunto de dados “osseus_dataset.csv” (Tabela 1) contém dados elementares relacionados a fatores de risco e exames realizados por indivíduos no Estado do Rio Grande do Norte, Brasil, para a investigação da densidade mineral óssea. Os dados foram coletados por meio do EPR do HUOL/UFRN, DXA e OSSEUS, um dispositivo de baixo custo baseado em ondas eletromagnéticas, que mede a atenuação do sinal ao atravessar a falange medial do dedo médio (PINHEIRO et al., 2021, ALBUQUERQUE et al., 2022).   Table 1: Description of Dataset Features. <div> <table> <tbody> <tr> <td> Attributes </td> <td> Description </td> <td> datatype  </td> <td> Value </td> </tr> <tr> <td> Electronic Patient Record (EPR) </td> </tr> <tr> <td> id </td> <td> Unique identifier for a person (anonymous). </td> <td> Categorical.  </td> <td> Person unique identifier. </td> </tr> <tr> <td> gender </td> <td> It informs the person's gender. </td> <td> Categorical. </td> <td> <ul> <li> female </li> <li> male </li> </ul> </td> </tr> <tr> <td> age </td> <td> It informs the person's age. </td> <td> Numerical. </td> <td> Integer value for age </td> </tr> <tr> <td> weight </td> <td> Informs the value referring to the person's weight—the unit of mass in kilogram (kg). </td> <td> Numerical. </td> <td> Integer value for weight </td> </tr> <tr> <td> height </td> <td> Informs the value relating to the person's height—the unit of measurement for size in centimeters (cm). </td> <td> Numerical. </td> <td> Integer value for height </td> </tr> <tr> <td> ethnicity </td> <td> Informs the person's ethnicity. </td> <td> Categorical. </td> <td> <ul> <li> black </li> <li> brown </li> <li> white </li> </ul> </td> </tr> <tr> <td> target </td> <td> Describe the person's diagnosis or medical report. </td> <td> Categorical.  </td> <td> <ul> <li> normal </li> <li> osteoporosis </li> <li> low bone mineral density </li> </ul> </td> </tr> <tr> <td> alcohol </td> <td> It informs whether the person consumes alcoholic beverages. </td> <td> Categorical. </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> smoking </td> <td> Informs whether the person is a smoker. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> activity </td> <td> It informs whether the person practices physical activities. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> milk </td> <td> It informs whether the person consumes dairy drinks. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> calcium </td> <td> It informs whether the person uses calcium. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> vitamin_d </td> <td> It informs whether the person uses Vitamin D. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> fall </td> <td> It informs whether the person has a history of falling. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> parents_osteoporosis </td> <td> It informs whether the person has a family history of osteoporosis. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> parents_curved </td> <td> It informs whether the person has a family history of "parents curved." </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> corticosteroids </td> <td> It informs whether the person uses corticosteroid-type medications for three months or longer. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> arthritis </td> <td> Informs if the person has arthritis. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> diseases </td> <td> Informs if the person has comorbidities. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> menopause </td> <td> Informs if the person has menopause. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> testosterone </td> <td> It informs whether the person uses testosterone. </td> <td> Categorical.  </td> <td> <ul> <li> yes </li> <li> no </li> </ul> </td> </tr> <tr> <td> OSSEUS (Osteoporosis screening based on electromagnetic waves) </td> </tr> <tr> <td> medial_length </td> <td> Length of the medial phalanx in mm. </td> <td> Numerical.  </td> <td> Integer value for length. </td> </tr> <tr> <td> medial_height </td> <td> Height of the medial phalanx in mm. </td> <td> Numerical. </td> <td> Integer value for height. </td> </tr> <tr> <td> medial_width </td> <td> Width of the medial phalanx in mm. </td> <td> Numerical. </td> <td> Integer value for width. </td> </tr> <tr> <td> calibration </td> <td> Osseus signal strength with no obstacle between the antennas. </td> <td> Numerical. </td> <td> Float value for calibration. </td> </tr> <tr> <td> attenuation </td> <td> Osseus signal strength with obstacles between antennas. </td> <td> Numerical. </td> <td> Float value for attenuation. </td> </tr> <tr> <td> DXA (Dual-energy x-ray absorptiometry) </td> </tr> <tr> <td> spine_deviation </td> <td> Reports the spinal standard deviation score that represents the difference between bone density and the expected value. </td> <td> Numerical.  </td> <td> Float value for deviation. </td> </tr> <tr> <td> femur_deviation </td> <td> Reports the femur standard deviation score that represents the difference between bone density and the expected value. </td> <td> Numerical.  </td> <td> Float value for deviation. </td> </tr> <tr> <td> body_deviation </td> <td> Reports the full body standard deviation score that represents the difference between bone density and the expected value. </td> <td> Numerical.  </td> <td> Float value for deviation. </td> </tr> <tr> <td> forearm_deviation </td> <td> Reports the forearm standard deviation score that represents the difference between bone density and the expected value. </td> <td> Numerical.  </td> <td> Float value for deviation. </td> </tr> <tr> <td> worst_deviation </td> <td> Reports the worst standard deviation score among all deviations obtained from the record. </td> <td> Numerical.  </td> <td> Float value for deviation. </td> </tr> </tbody> </table>     </div> REFERENCES Albuquerque, G. et al. A method based on non-ionizing microwave radiation for ancillary diagnosis of osteoporosis: a pilot study. BioMedical Eng. OnLine 21, 70, https://doi.org/10.1186/s12938-022-01038-y (2022). Pinheiro, B. d. M. et al. The influence of antenna gain and beamwidth used in osseus in the screening process for osteoporosis. Sci. Reports 11, 19148, https://doi.org/10.1038/s41598-021-98204-4 (2021). <div>   </div>

opencc-by-4.0Dec 2024View details →

zenodo40/100

HDAC6 screening dataset using tau-based substrate in an enzymatic assay yields selective inhibitors and activators

Structure and information of the data file DATA SET; Contains the information to which data set this information belongs. There are four possibilities denoted 1 to 4. Data set1: Enzymatic assay of human HDAC6 with commercial peptide substrate. Data set2: Enzymatic assay of human HDAC6 with custom peptide substrate. Data set3: Hit confirmation of the active molecules of the enzymatic assay of human HDAC6 with custom peptide substrate. Data set4: Determination of IC50 values for inhibition of enzymatic assay of human HDAC6 with custom peptide substrate. INTERNAL NAME; An internal name which enables identification of the compound within data sets from Fraunhofer ITMP ScreeningPort. TYPE; Type of data. Either 'inhibition' for normalized inhibition values or 'IC50' for enzymatic IC50. RELATION; Relation between TYPE and VALUE, always '='. VALUE; Value of the normalized inhibition or the enzymatic IC50. UNITS; Unit of the value. Either '%' for the normalized inhibition or 'uM' for the enzymatic IC50. NAME; Trade name of the chemical compound. SMILES; The canonical Smile of the chemical compound.   Abstract Histone deacetylase 6 (HDAC6) and HDAC10 are unique among the other HDACs as they consist of two domains instead of one. Only in the case of HDAC6 both domains are active resulting in a number of unique deacetylase reactions. Interestingly, HDAC6 can regulate the microtubule network and plays a role in the degradation of misfolded and aggregated proteins. We therefore developed a substrate (Boc-Ile-Asp-(Dimethyl)Lys-(Ac)Lys-aminoluciferin) based on a critical acetylation site of misfolded human Tau, a hallmark of Alzheimer’s Disease. This substrate was used to screen a 5632 compound encompassing repurposing library at 10 µM in a coupled, luminescence based assay. The assay was miniaturised to 10 µL per enzymatic reaction. For comparison, a generic HDAC substrate (BOC-Gly-(Ac)Lys-aminoluciferin) was also used to screen the same library. Both substrates rely on a cascade of enzymatic reactions. First, HDAC6 deacetylates the substrate followed by cleavage of aminluciferin from the peptide by porcine Trypsin and conversion of the aminoluciferin using firefly Luciferase. Compounds with an activity of at least 75% inhibition against the custom human Tau based substrate were confirmed in triplicates at the screening concentration of 10 µM. Confirmed hits, activity of at least 75%, where analysed in 8 point or 15 point dose response curves, depending on their activity. The data presented here encompass both primary data sets including 5632 compounds as well as 249 values from hit confirmation screening against the hTau based substrate and 151 IC50 values from confirmed hits.   Methods of data generation Enzymatic assay of human HDAC6 with commercial peptide substrate. The assay using the commercial peptide substrate (BOC-Gly-(Ac)Lys-aminoluciferin) was obtained from Promega Inc.. In the beginning the assay buffer is thawed and the lyophilized substrate is dissolved according to the technical manual (Promega Inc.) to create the substrate reagent. HDAC6 (obtained from BPS Biosciences) is dissolved in assay buffer at 0.2 nM, which is twice the final assay concentration. Compounds and controls are added to the plates using acoustic dispensing to reach a final concentration of 10 µM in the assay followed by 5 µl enzyme solution per well. Plates are centrifuged shortly and incubated for 10 min at RT. Afterwards, 5 µL/well substrate solution are added to the wells, centrifuged shortly and incubated for 10 min prior detection of the luminescence signal on a multimode reader. Primary screening was done at one concentration (10 µM) in singlicates.   Enzymatic assay of human HDAC6 with custom peptide substrate. The assay was designed based on a commercial HDAC6 assay available from Promega Inc. This luminescence assay works by an aminoluciferin coupled HDAC6 peptide substrate. Upon deacetylation of the peptidic substrate by HDAC6 (obtained from BPS Biosciences) Trypsin (obtained from Sigma-Aldrich) can cleave the aminoluciferine from the peptide which can be converted by Luciferase (obtained from AAT Bioquest) to the detected signal. First, a twofold concentrated enzyme solution was generated, consisting of 4 nM HDAC6 and 0.1% BSA in HEPES buffer (25 mM HEPES, 137 mM NaCl, 2.7 mM KCl and 1 mM MgCl2, pH 7.0). Second, a twofold peptide solution was generated containing 100 µM custom made peptide (Boc-Ile-Asp-(Dimethyl)Lys-(Ac)Lys-aminoluciferin) in HEPES buffer. Compounds and controls are added to the plates using acoustic dispensing to reach a final concentration of 10 µM in the assay followed by 5 µl enzyme solution per well. Plates are centrifuged shortly and 5 µL/well peptide solution are added to the wells, centrifuged shortly and incubated for 30 min at RT. Afterwards, 5 µL detection reagent (0.067 mg/mL Luciferase, 133.3 µM ATP, 0.133 mg/mL Trypsin in HEPES buffer) were added to each well. Plates were centrifuged shortly and measured on a multimode reader after 30 min incubation at RT in the dark. Primary screening was done at one concentration (10 µM) in singlicates.   Hit confirmation of the active molecules of the enzymatic assay of human HDAC6 with custom peptide substrate The assay was designed based on a commercial HDAC6 assay available from Promega Inc. This luminescence assay works by an aminoluciferin coupled HDAC6 peptide substrate. Upon deacetylation of the peptidic substrate by HDAC6 (obtained from BPS Biosciences) Trypsin (obtained from Sigma-Aldrich) can cleave the aminoluciferine from the peptide which can be converted by Luciferase (obtained from AAT Bioquest) to the detected signal. First, a twofold concentrated enzyme solution was generated, consisting of 4 nM HDAC6 and 0.1% BSA in HEPES buffer (25 mM HEPES, 137 mM NaCl, 2.7 mM KCl and 1 mM MgCl2, pH 7.0). Second, a twofold peptide solution was generated containing 100 µM custom made peptide (Boc-Ile-Asp-(Dimethyl)Lys-(Ac)Lys-aminoluciferin) in HEPES buffer. Compounds and controls are added to the plates using acoustic dispensing to reach a final concentration of 10 µM in the assay followed by 5 µl enzyme solution per well. Plates are centrifuged shortly and 5 µL/well peptide solution are added to the wells, centrifuged shortly and incubated for 30 min at RT. Afterwards, 5 µL detection reagent (0.067 mg/mL Luciferase, 133.3 µM ATP, 0.133 mg/mL Trypsin in HEPES buffer) were added to each well. Plates were centrifuged shortly and measured on a multimode reader after 30 min incubation at RT in the dark. Hit confirmation was done at one concentration (10 µM) in triplicates.   Determination of IC50 values for inhibition of enzymatic assay of human HDAC6 with custom peptide substrate The assay was designed based on a commercial HDAC6 assay available from Promega Inc. This luminescence assay works by an aminoluciferin coupled HDAC6 peptide substrate. Upon deacetylation of the peptidic substrate by HDAC6 (obtained from BPS Biosciences) Trypsin (obtained from Sigma-Aldrich) can cleave the aminoluciferine from the peptide which can be converted by Luciferase (obtained from AAT Bioquest) to the detected signal. First, a twofold concentrated enzyme solution was generated, consisting of 4 nM HDAC6 and 0.1% BSA in HEPES buffer (25 mM HEPES, 137 mM NaCl, 2.7 mM KCl and 1 mM MgCl2, pH 7.0). Second, a twofold peptide solution was generated containing 100 µM custom made peptide (Boc-Ile-Asp-(Dimethyl)Lys-(Ac)Lys-aminoluciferin) in HEPES buffer. Compounds and controls are added to the plates using acoustic dispensing to reach a final concentration of 10 µM in the assay followed by 5 µl enzyme solution per well. Plates are centrifuged shortly and 5 µL/well peptide solution are added to the wells, centrifuged shortly and incubated for 30 min at RT. Afterwards, 5 µL detection reagent (0.067 mg/mL Luciferase, 133.3 µM ATP, 0.133 mg/mL Trypsin in HEPES buffer) were added to each well. Plates were centrifuged shortly and measured on a multimode reader after 30 min incubation at RT in the dark. IC50 values were determined using 7 point dose response curves (DRCs) between 20 µM and 312 nM. In case inhibition values were not below 50% additional 7 point DRCs were measured, starting at 312 nm with a dilution factor of 2. All DRCs were recorded in triplicates.

opencc-by-4.0Oct 2021View details →

zenodo40/100

A Multiplexed Cell-Free Assay to Screen for Antimicrobial Peptides in Double Emulsion Droplets

Data underlying the figures in the publication “A Multiplexed Cell-Free Assay to Screen for Antimicrobial Peptides in Double Emulsion Droplets”, published in Angew. Chem. Int. Ed., 2022, e202114632. <a href="https://onlinelibrary.wiley.com/doi/10.1002/anie.202114632">https://onlinelibrary.wiley.com/doi/10.1002/anie.202114632</a>   Table of contents: 1. Figure 1b: Bright-field image of the double emulsions droplets produced on the microfluidic chip (scale bar 40 μm). 2. Figure 1c: Source video of the image in Figure 1c. Overlaid fluorescence and bright-field image of a double emulsion in a hydrodynamic trap, containing LUVs loaded with a self-quenching concentration of SRB in the cell-free extract, showing background fluorescence (scale bar 20 μm). 3. Figure 2a: Excel file containing the experimental data for Figure 2a. Cell-free protein production. Cell-free production of sfGFP in double emulsion (DE) droplets. The expression and folding of sfGFP was confirmed by the increase of fluorescence at 516 nm (ex. 488 nm). The dashed ribbon represents standard deviation (n=150). 4. Figure 2c: Excel files containing the experimental data for Figure 2c. Mean fluorescence intensities of b) after incubation at room temperature for 16 hours. no DNA: DEs without any alpha-hemolys in plasmid DNA(n=107), α-HL:DEs with the alpha-hemolys in plasmid DNA(n=258), SDS: double emulsions without any alpha-hemolys in plasmid DNA, exposed to a solution of 0.5% SDS in buffer throughout the incubation (n=204). 5. Figure 2d: Excel file containing the experimental data for Figure 2d. Fluorophore leakage kinetics from mammalian-like LUVs with SRB and from bacteria-like LUVs with 6-FAM, induced by the cell-free expression of pneumolysin in a 384 well-plate, starting at time 0. Fractional fluorescence (fF) is calculated by setting the zero level to the vesicle fluorescence in the absence of DNA, and the maximum level of fluorescence, scaled to a value of 1, to the value obtained by lysing the vesicles with 0.5% SDS. Solid lines represent the average of three independent reactions visible below. 6. Figures 2e and 2f: FACS data for Figures 2e and 2f. 7. Figure 3a: Excel file containing the experimental data for Figure 3a.   Fluorophore leakage kinetics from mammalian-like LUVs with SRB and bacteria-like LUVs with 6-FAM, induced by the cell-free expression of meucin-25 in a 384 well-plate. Each well contained 8 nM of plasmid (Supporting Information Table 1). Solid lines represent the average of three technical replicates displayed as well (the lines are overlapping, thus not visible). 8. Figure 3c: Excel file containing the experimental data for Figure 3c.   Bacterial viability assay with increasing meucin-25 concentrations, measured by flow cytometry. Propidium iodide (PI) cannot pass intact bacterial membranes and only intercalates the DNA of permeabilized dead bacteria (“PI positive”). Constitutively expressed sfGFP proteins normally efficiently retained in intact bacterial cells (“GFPpositive”) but lost in suitably permeabilized cells. Error bars indicate standard deviation (n=10000). 9. Figure SI_2: Excel files containing the experimental data for Supplementary Figure 2. 10. Figure SI_3: Excel file containing the experimental data for Supplementary Figure 3. 11. Figure SI_4a: Excel files containing the experimental data for Supplementary Figure 4a. 12. Figure SI_4b: Excel files containing the experimental data for Supplementary Figure 4b. 13. Figure SI_5: Excel files containing the experimental data for Supplementary Figure 5. 14. Figure SI_6: Excel files containing the experimental data for Supplementary Figure 6.

opencc-by-4.0Feb 2022View details →

zenodo40/100

Application of multi-analyte / multi-matrix screening method for pesticide residues in fruits and vegetables to Interaboratory Comparison Study on Pesticide Residues in Food (ILC)

The suitability of multi-analyte / multi-matrix screening method for pesticide residues in fruits and vegetables and related products, developed within activities of task (Multi-analyte / multi-matrix screening method for pesticide residues in fruits and vegetables (including tea) and fruit juices), was evaluated by the Interaboratory Comparison Study on Pesticide Residues in Food (ILC).  Test material (“Pesticide Residues in green tea”), prepared from the batch used for another proficiency test (PT), was provided by Fapas (Fera Science Ltd, York, UK). Data set obtains (i) information about performance characteristics of the analytical method and (ii) compilation of results of interlaboratory study.

opencc-by-4.0Feb 2022View details →

zenodo40/100

In vivo screening for functional HIF2A enhancers in renal carcinoma.

High throughput sequencing data and analysis from a CRISPRi-based in vivo functional screen for oncogenic HIF2A-bound transcriptional enhancers in renal cancer.

opencc-by-4.0Mar 2022View details →

zenodo40/100

Computational Analysis of Two-dimensional High-throughput Data from Large-scale RNAi Screens and Single-cell Transcriptomics

This publication provides a singularity definition file to reproduce the computational environment along with the scripts to reproduce every figure or table in the revised manuscript using ZetaSuite Perl module and R package. First, generate a new folder and then download all the files into the folder. Then, uncompressed the files DataSets_part1.tar.gz,DataSets_part2.tar.gz,DataSets_part3.tar.gz,DataSets_part4.tar.gz, and scripts.tar.gz. within the folder. Next, move all the files in DataSets_part1 folder, DataSets_part2 folder,DataSets_part3 folder and DataSets_part4 folder to a new folder called DataSets. Finally, run the following scripts to generate the figures and tables in our manuscript. Regeneration of Figure2 and S2: singularity exec ZetaSuite.sif sh Figure2andS2.sh   Regeneration of Figure3 and S3: singularity exec ZetaSuite.sif sh Figure3andS3.sh   Regeneration of Figure4 and S4: singularity exec ZetaSuite.sif sh Figure4andS4.sh   Regeneration of Figure5 and S5: singularity exec ZetaSuite.sif sh Figure5andS5.sh   Regeneration of Figure6 and S6: singularity exec ZetaSuite.sif sh Figure6andS6.sh   Regeneration of Figure7 and S7: singularity exec ZetaSuite.sif sh Figure7andS7.sh

opencc-by-4.0Mar 2022View details →

zenodo40/100

Screening routine for integrative dynamic structural biology using SAXS and intramolecular FRET and DEER-EPR on hGBP1 (human guanalyte binding protein 1)

Initial and selected ensemble for major and minor species of the human guanalyte binding protein 1 with scripts for the reading routine to combine and analyse jointly SAXS, EPR and FRET data.

opencc-by-4.0May 2022View details →

zenodo40/100

Virtual screening on Nsp16: screening of 1084 compounds in VeroE6-eGFP cells

This report describes the most relevant results of virtually screening the Janssen Pharmaceutica compound collection for potential activity against SARS-CoV-2 Nsp16 and confirmation of potential hits in a VeroE6 cell-based anti-SARS-CoV-2 assay.

opencc-by-4.0Jun 2022View details →

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Screening of 2694 RdRP virtual screening hits in RdRP/Nsp7/Nsp8 biochemical assay and confirmation in cellular SARS-CoV-2 assay

This report describes the most relevant results of virtually screening the Janssen Pharmaceutica compound collection for potential activity against SARS-CoV-2 RNA polymerase and confirmation of potential hits in a biochemical SARS-CoV RTC assay and A549-hACE2 cell-based anti-SARS-CoV-2 assay.

opencc-by-4.0Jun 2022View details →

zenodo40/100

Raw data: High-throughput screening of soybean di-nitrogen fixation and seed nitrogen content using spectral sensing

Symbiotic di-nitrogen fixation of grain legumes has a substantial impact on crop performance, harvest product quality, and nitrogen (N) balance of crop rotations, particularly under organic management regimes. In soybean breeding, selection for increased nitrogen fixation is desirable for improving seed protein content and N balance of cropping systems. However, the lack of high-throughput screening methods for direct measurement of N 2 fixation rates prohibits practical breeding efforts. Therefore, hyperspectral canopy reflectance measurement as a field-based phenotyping method was evaluated in three environments for indirect estimation of N fixation and uptake of soil nitrogen in a set of early maturity soybean genotypes exhibiting a wide range in seed protein content. Reflectance spectra were collected in repeated measurements during flowering and early seed filling stages. Subsequently, various spectral reflectance indices (SRIs) were calculated for characterizing nitrogen accumulation of individual genotypes. Moreover, prediction models for seed protein content as an end-of-season target trait were developed utilizing full spectral information in partial-least-square regression (PLSR) models. A number of N-related SRIs calculated from spectral reflectance data recorded at the beginning of the seed filling stage were significantly correlated to seed protein content. The best prediction of seed protein content, however, was achieved in PLSR models (validation R 2 =0.805 across all three environments). Environments lower in initial soil mineral N content appeared as more favorable selection sites in terms of prediction accuracy, because N fixation is not masked by soil N uptake in such environments. Hyperspectral reflectance data proved to be a valuable method for determining genetic variation in crop N accumulation, which might be implemented in high-throughput screening protocols for N fixation in plant breeding programs.

opencc-by-4.0Jun 2022View details →

zenodo40/100

Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening

Modeled structure of IFITM3 and Desmond MD trajectory files for IFITM3 and IFITM3-ligand complexes. Please see README file.

opencc-by-4.0Jul 2022View details →

zenodo40/100

Dataset for the TBK1 antibody screening study

This antibody characterization dataset is related to the F1000 research article openly available at F1000Research. This project contains the following underlying data included in a study aiming at characterization antibodies for the serine/threonine-protein kinase (TBK1) protein, encoded by the TBK1 gene. The original study is also available on the Zenodo YCharOS community (<a href="https://doi.org/10.5281/zenodo.6402968">https://doi.org/10.5281/zenodo.6402968</a>) and on BioRxiv (<a href="https://doi.org/10.1101/2022.06.03.494699">https://doi.org/10.1101/2022.06.03.494699</a>). File name is presented as "database number"_"company catalogue number".

opencc-by-4.0Jul 2022View details →

zenodo40/100

A hydroponics based high throughput screening system for clubroot disease pathotyping

Clubroot is a devastating disease affecting the canola industry and caused by the protist Plasmodiophora brassicae. Since the 1940s, several pathotyping systems have been developed and different classifications have been used to differentiate P. brassicae isolates based on their ability to infect different hosts. Unfortunately, none of previously developed pathotyping systems discriminate virulent and avirulent isolates of P. brassicae against the clubroot resistance profiles of commercially available canola cultivars. To try to solve this limitation we have developed a hydroponic-based bioassay using P. brassicae single spore isolates (SSIs), and four canola inbreed homozygous lines (CIH). These SSIs are representative of the virulence widely spread in the field, while these CIH are representative of the resistance commercially available to growers. Through this new phenotyping scheme, we have been able to connect P. brassicae isolates with their ability to break down clubroot resistance in canola in shorter time and economically more efficiently. This will help to tailor the selection of resistant canola varieties to use in an infested field for the longest possible time, empowering producers to make informed decisions about the best canola cultivar to use based on the P. brassicae diversity in their field

opencc-by-4.0Jul 2022View details →

zenodo40/100

PSnpBind: A database of mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow

A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. These effects have been studied on very limited and small datasets while, ideally, a large dataset of binding affinity changes due to binding site single-nucleotide polymorphisms (SNPs) is needed for evaluation. However, to the best of our knowledge, such a dataset does not exist. Thus, a reference dataset of ligands binding affinities to proteins with all their reported binding sites’ variants was constructed using a molecular docking approach. Having a large database of protein-ligand complexes covering a wide range of binding pocket mutations and a large small molecules’ landscape is of great importance for several types of studies. For example, developing machine learning algorithms to predict protein-ligand affinity or a SNP effect on it requires an extensive amount of data. In this work, we present PSnpBind: A large database of mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow. It provides a web interface to explore and visualize the protein-ligand complexes and a REST API to programmatically access the different aspects of the database contents. PSnpBind is freely available at <a href="https://psnpbind.org">https://psnpbind.org</a>. The source code of the tools used in constructing PSnpBind is available on <a href="https://github.com/ammar257ammar/PSnpBind-Build">GitHub</a>.

opencc-by-4.0Jul 2021View details →

dryad40/100

Feasibility and acceptability of personalized breast cancer screening (DECIDO Study): A single-arm proof-of-concept trial

The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40–50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.

opencc-zeroSep 2022View details →

zenodo40/100

PanDDA analysis of PTP1B screened against fragment libraries

Tyrosine phosphatase, PTP1B, screened against multiple fragment libraries via X-ray crystallography.

opencc-by-4.0Nov 2017View details →

zenodo40/100

Analog Series of Compounds with High Frequency of Activity in Screening Assays

A set of 6941 analog series and associated data are provided. These series exclusively consist of compounds that are most frequently active across public screening assays.

opencc-by-4.0Nov 2017View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record