Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
564
datasets available to search
ShareScore release 0.9.0
Dataset results
564 results for “ABS”
Figure 7 from: Laksmiani NPL, Widiantara IWA, Pawarrangan ABS (2022) Potency of moringa (Moringa oleifera L.) leaves extract containing quercetin as a depigmentation agent inhibiting the tyrosinase enzyme using in-silico and in-vitro assay. Pharmacia 69(1): 85-92. https://doi.org/10.3897/pharmacia.69.e73132
Figure 7 Dopachrome spectrum using spectrophotometry UV-VIS.
Figure 2 from: Laksmiani NPL, Widiantara IWA, Pawarrangan ABS (2022) Potency of moringa (Moringa oleifera L.) leaves extract containing quercetin as a depigmentation agent inhibiting the tyrosinase enzyme using in-silico and in-vitro assay. Pharmacia 69(1): 85-92. https://doi.org/10.3897/pharmacia.69.e73132
Figure 2 2D Chemical structure of quercetin (a), 3D chemical structure of quercetin (b).
Figure 9 from: Laksmiani NPL, Widiantara IWA, Pawarrangan ABS (2022) Potency of moringa (Moringa oleifera L.) leaves extract containing quercetin as a depigmentation agent inhibiting the tyrosinase enzyme using in-silico and in-vitro assay. Pharmacia 69(1): 85-92. https://doi.org/10.3897/pharmacia.69.e73132
Figure 9 Tyrosinase inhibition (%) curve of moringa leaves extract.
Figure 8 from: Laksmiani NPL, Widiantara IWA, Pawarrangan ABS (2022) Potency of moringa (Moringa oleifera L.) leaves extract containing quercetin as a depigmentation agent inhibiting the tyrosinase enzyme using in-silico and in-vitro assay. Pharmacia 69(1): 85-92. https://doi.org/10.3897/pharmacia.69.e73132
Figure 8 Tyrosinase inhibition (%) curve of kojic acid.
Electronic structure fingerprints of nickel-cobalt-manganese oxide from x-ray spectroscopy and high-throughput ab initio calculations
<p>AiiDA archives of the calculations presented in the paper "Electronic structure fingerprints of nickel-cobalt-manganese oxide from x-ray spectroscopy and high-throughput <em>ab initio</em> calculations".</p> <p> </p> <ul> <li>structures_and_general_info.aiida: The "EnumlibCalcJob" to generate the structural candidates, the resulting initial structures and AiiDA "Dict" nodes containing the mapping of the different steps (via their corresponding <em>uuid</em>) to each structure.</li> <li>pre_optimization.aiida: The relevant calculations to perform the pre-relaxation.</li> <li>optimization.aiida: The relevant calculations to perform the final structural optimization.</li> <li>electronic_structure.aiida: The bandstructure and DOS/PDOS calculations. All preliminary calculations such as SCF and NSCF calculations to obtain the eigenvalues are included as well.</li> </ul> <p>Finally, the Pandas DataFrame containing the PDOS for each site of all the structures (resolved into orbital and spin contributions) which builds the foundation for the presented analysis is stored in the `pickle` format in `pdos_all.pckl`.</p>
Figure 2 from: Drazen JC, Smith CR, Gjerde K, Au W, Black J, Carter G, Clark M, Durden JM, Dutrieux P, Goetze E, Haddock S, Hatta M, Hauton C, Hill P, Koslow J, Leitner AB, Measures C, Pacini A, Parrish F, Peacock T, Perelman J, Sutton T, Taymans C, Tunnicliffe V, Watling L, Yamamoto H, Young E, Ziegler AF (2019) Report of the workshop Evaluating the nature of midwater mining plumes and their potential effects on midwater ecosystems. Research Ideas and Outcomes 5: e33527. https://doi.org/10.3897/rio.5.e33527
Figure 2 The principle midwater ecosystems across depth and some pertinent characteristics of each.
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk (sequence model release)
<p>(This is the updated version that has been converted a standard pytorch model format)</p> <p>This is the deep learning sequence model used in </p> <p>Jian Zhou, Chandra L. Theesfeld, Kevin Yao, Kathleen M. Chen, Aaron K. Wong, and Olga G. Troyanskaya, Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk, Nature Genetics, 2018.</p> <p>Note the full software is available from https://github.com/FunctionLab/ExPecto and this release is created for the convenience of use and under the same non-commercial license. The model weights can be loaded with pytorch load_state_dict function (for an example please find <a href="https://github.com/FunctionLab/ExPecto/blob/master/chromatin.py">https://github.com/FunctionLab/ExPecto/blob/master/chromatin.py</a>). We also provide a web server for browsing mutations with strong predicted effects at https://hb.flatironinstitute.org/expecto/, which are currently limited to mutations within 1kb to TSS or are 1000 Genomes variants.</p> <p>Trivia: we code-named our models with whale names. This model has an unofficial codename DeepSEA "Beluga".</p>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 6 (1-83).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 3 (1-60).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 2 (1-60).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 1 (51-91) and 8 (1-5).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 3 (61-120).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 4 (41-55).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 4 (1-40).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 7 (1-51).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 2 (61-118).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
AlphaFold_ab_initio iterative structure predictions sub trajs for faster download
<p>PDB ids start from 5 (1-73).</p> <div> <p>Check related biorxiv preprint: AlphaFold2 knows some protein folding principles; DOI: https://doi.org/10.1101/2024.08.25.609581.</p> <p> </p> </div>
sulphate and molybdate incorporation at calcite-water interface - ab initio molecular dynamics data
<p>Provided here are ab initio molecular dynamics data files generated in CP2K, relating to the publication entitled<br> Sulphate and Molybdate Incorporation at the Calcite-Water Interface: Insights from Ab Initio Molecular Dynamics. By Scott D. Midgley, Devis Di Tommaso, Dominik Fleitmann, Ricardo Grau-Crespo.</p> <p>We have provided the CP2K input file (.inp), the CP2K energy file (.ener), and a single geometry snapshot from the simulation (.xyz).<br> It is not possible to share the fully dynamics trajectory, because each file is extremely large.</p> <p>N.B. for the sulphate ion in water, a corruption in the .ener file meant that it was not possible to share. Instead a list of MD energies are given as a .txt file, with energies in eV.<br> </p>
Free and defect-bound (bi)polarons in LiNbO3: Atomic structure and spectroscopic signatures from ab initio calculations
<p>Dataset of the publication “Free and defect-bound (bi)polarons in LiNbO<sub>3</sub>: Atomic structure and spectroscopic signatures from ab initio calculations“, F. Schmidt, A. L. Kozub, T. Biktagirov, C. Eigner, C. Silberhorn, A. Schindlmayr, W. G. Schmidt, and U. Gerstmann, Physical Review Research 2, 043002 (2020) ( <a href="https://doi.org/10.1103/PhysRevResearch.2.043002">https://doi.org/10.1103/PhysRevResearch.2.043002</a> ). The tar file includes the data on which the plots shown in figures 2, 3, 4, 6, 7, 8, and 9 are based.</p>
Figure 1 from: Arathi AR, Oliver PG, Ravinesh R, Kumar AB (2018) The Ashtamudi Lake short-neck clam: re-assigned to the genus Marcia H. Adams & A. Adams, 1857 (Bivalvia, Veneridae). ZooKeys 799: 1-20. https://doi.org/10.3897/zookeys.799.25829
Figure 1 Sampling locations of venerid clams from the coast of southern India.
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.