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.
3,655
datasets available to search
ShareScore release 0.9.0
Dataset results
3,655 results for “Structural data”
Data table 4 from publication "Impaired interactions of ataxin-3 with protein complexes reveals their specific structure and functions in SCA3 Ki150 model" (doi.org/10.3389/fnmol.2023.1122308)
<div>An Excel table contains a list of proteins identified by MS from a pull-down experiment using cerebellum lysates with Dynabeads coated with anti-ataxin-3 1H9 mouse monoclonal antibodies. The false positive interactor proteins were excluded from this list by subtracting proteins found in "Supplementary_table 3_cerebellum isogenic mouse IgG control dynabeads.xlsx<span><br></span></div>
Data table 2 from publication "Impaired interactions of ataxin-3 with protein complexes reveals their specific structure and functions in SCA3 Ki150 model" (doi.org/10.3389/fnmol.2023.1122308)
<p>An excel table containing a list of proteins identified by MS from samples after a pull-down experiment using cerebral cortex lysates with Dyna beads coated with control isogenic mouse IgG. The proteins from the list were considered false positive interactors of ataxin-3 in the cortex.</p>
Data table 1 from publication "Impaired interactions of ataxin-3 with protein complexes reveals their specific structure and functions in SCA3 Ki150 model" (doi.org/10.3389/fnmol.2023.1122308)
<p>An excel table contains LFQ intensity and other raw MS data for proteins identified in fractions 3,4,5 (i), 11, 12, 13, (ii) 18, 19, and 20 (iii) from ki150 and ki21 model brains. These fractions showed enrichment in ATXN3 protein. The fractions are visualized in Figure 4 (<a href="http://doi.org/10.3389/fnmol.2023.1122308" target="_blank" rel="noopener">doi.org/10.3389/fnmol.2023.1122308</a>)</p>
Supplementary data and code to "Cellular location shapes quaternary structure of enzymes" by György Abrusán and Aleksej Zelezniak
<p>Scripts and high-level data to reproduce the figures and supplementary figures of "Cellular location shapes quaternary structure of enzymes" by György Abrusán and Aleksej Zelezniak. <em>Nature Communications</em> (2024) 15:8505.</p>
Computational data for Structure of G protein-coupled receptor GPR1 bound to full-length chemerin adipokine reveals a chemokine-like reverse binding mode
<p>MD simulation data for the research article titled "Structure of G protein-coupled receptor GPR1 bound to full-length chemerin adipokine reveals a chemokine-like reverse binding mode".</p>
Data from: Built structures influence patterns of energy demand and CO2 emissions across countries
Open the record for dataset details and reuse information.
Data Supporting "Air-Sea Momentum Exchange with Explicit Wind-Wave-Current Coupling and Effects on Hurricane Structure and Impacts"
<p>This dataset produced the figures for the Air-Sea Momentum Exchange with Explicit Wind-Wave-Current Coupling and Effects on Hurricane Structure and Impacts Manusrcipt.</p>
Coarse-Grained and Multi-Dimensional Data-Driven Molecular Generation: A Structure-Based Framework for Selective Inhibitor Design and Optimization
<p><span>Many approaches not only fail to consider the intricate binding pocket interactions, leading to molecules with suboptimal properties and stability, but also struggle with designing selective inhibitors. To address this challenge, we have developed an innovative structure-based three-dimensional molecular generation framework named </span><span>Coarse-grained and Multi-dimensional Data-driven molecular generation (CMD-GEN). This framework bridges three-dimensional ligand-protein complex data with two-dimensional drug-like molecule data by utilizing coarse-grained pharmacophore points sampled from diffusion models, thereby enriching the training data for generative models.</span> <span>Through a hierarchical architecture, it decomposes the generation of three-dimensional molecules within the pocket into sampling of coarse-grained pharmacophore points, generating of chemical structures, and alignment of conformations, avoiding the instability issues associated with inherent in deep generative model-based generation of molecular conformations.<br><br>This project provide the source dataset used to train and evaluate the overall model.<br></span></p>
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics: Data and Models
<p>This repository contains data and models used in the following paper.</p> <p>Swanson, K., Liu, G., Catacutan, D., Zou, J. & Stokes, J. <a href="https://www.nature.com/articles/s42256-024-00809-7">Generative AI for designing and validating easily synthesizable and structurally novel antibiotics</a>. <em>Nature Machine Intelligence, </em>2024.</p> <p>The data and models are meant to be used with the <a href="https://github.com/swansonk14/SyntheMol">SyntheMol</a> code. More details about how to use the data and models with the code are available <a href="https://github.com/swansonk14/SyntheMol/tree/main/docs">here</a>.</p> <p>The Data.zip file has the following structure. Note that the numbers for the Data subdirectories correspond to the supplementary data numbers in the paper (e.g., 1_training_data corresponds to Supplementary Data 1).</p> <p>Data</p> <p> 1_training_data: The <em>Acinetobacter baumannii</em> inhibition data used to train antibiotic property prediction models.</p> <p> 2_chembl: Known antibiotic and antibacterial molecules from <a href="https://www.ebi.ac.uk/chembl/">ChEMBL</a>, which are used to compute the novelty of generated antibiotic candidates.</p> <p> 4_real_space: Data files and statistics for the <a href="https://enamine.net/compound-collections/real-compounds/real-space-navigator">Enamine REAL Space</a>. The molecular building blocks file is version 2021 q3-4 while all other REAL Space details are computed from the full enumerated REAL space version 2022 q1-2 (downloaded on August 30, 2022).</p> <p> 5_generations_clogp: Compounds generated by SyntheMol using Chemprop models trained to predict cLogP.</p> <p> 6_generations_chemprop: Compounds generated by SyntheMol using Chemprop models trained to predict <em>A. baumannii</em> inhibition.</p> <p> 7_generations_chemprop_rdkit: Compounds generated by SyntheMol using Chemprop-RDKit models trained to predict <em>A. baumannii</em> inhibition.</p> <p> 8_generations_random_forest: Compounds generated by SyntheMol using random forest models trained to predict <em>A. baumannii</em> inhibition.</p> <p> 9_synthesized: Information on the 58 SyntheMol-generated compounds that were successfully synthesized by Enamine.</p> <p>The Models.zip file contains one folder for each model used in the paper. Note that each model is technically an ensemble of ten individual models, so each directory contains ten model files.</p>
Data for manuscript: The structural influence of the oncogenic driver mutation N642H in the STAT5B SH2 domain
<p>The data is provided as a part of the manuscript "<strong>The structural influence of the oncogenic driver mutation N642H in the STAT5B SH2 domain</strong>". </p> <p>This repository includes an archive with folders:</p> <div> </div> <div>MD_Data</div> <div>-- Contains shortened versions of the MD trajectories, and initial structure files used to run simulations</div> <div> </div> <div>FigureData </div> <div>-- Contains comma separated value files for each figure</div> <p> </p>
Supplementary Data for: Benchmark of density functional theory in the prediction of chemical shielding anisotropies for anisotropic NMR based structural elucidation
<p>Additional Data for the research paper titled: Benchmark of density functional theory in the prediction of chemical shielding anisotropies for anisotropic NMR based structural elucidation.</p> <p>Anisotropy Benchmark for Carbon NS372:</p> <ul> <li>Chemical Shielding Tensor for the molecules in the NS372 test set for carbon (XLSX)</li> <li>Coordinate files for the molcules of the NS372 test set that contained carbon (in NS372-Carbon-COORD-Files.zip)</li> </ul> <p>DFT Benchmark for RCSA for Natural Products:</p> <ul> <li>Chemical Shielding Tensor used for the RCSA analysis of 6 Natural Products (CSV)</li> <li>Turbomole Input and Ouput files for the DFT calculation of the natural products (in RAW_DATA_for_RCSA_Analysis.zip)</li> <li>ConArch+ Input and Ouput files for the RCSA analysis using (in RAW_DATA_for_RCSA_Analysis.zip)</li> <li>Coordinate files used for the RCSA analysis (in RAW_DATA_for_RCSA_Analysis.zip)</li> </ul> <p> </p>
X-ray diffraction data on the crystal structures of Tris-bound β-glucosidase from Thermoanaerobacterium saccharolyticum
<p>X-ray diffraction data of Tris-bound β-glucosidase from Thermoanaerobacterium saccharolyticum</p> <p>Data type: raw data<br>Data format: cbf</p> <p>Data <br>1. TsaBgl-Tris Data I <br>2. TsaBgl-Tris Data II<br>3. TsaBgl-Tris Data III </p>
Data from: Parallel mechanisms signal a hierarchy of sequence structure violations in the auditory cortex
<p>The brain predicts regularities in sensory inputs at multiple complexity levels, with neuronal mechanisms that remain elusive. Here, we monitored auditory cortex activity during the local-global paradigm, a protocol nesting different regularity levels in sound sequences. We observed that mice encode local predictions based on stimulus occurrence and stimulus transition probabilities, because auditory responses are boosted upon prediction violation. This boosting was due to both short-term adaptation and an adaptation-independent surprise mechanism resisting anesthesia. In parallel, and only in wakefulness, VIP interneurons responded to the omission of the locally expected sound repeat at sequence ending, thus providing a chunking signal potentially useful for establishing global sequence structure. When this global structure was violated, by either shortening the sequence or ending it with a locally expected but globally unexpected sound transition, activity slightly increased in VIP and PV neurons respectively. Hence, distinct cellular mechanisms predict different regularity levels in sound sequences.</p>
Data and codes for "Habitat structural complexity increases age-class coexistence and population growth rate through relaxed cannibalism in medaka fish"
<p>The zip file contains readme files, as well as data and codes to reproduce results and figures from the paper.</p>
Data to estimate energy efficiency and environmental friendliness of Ukrainian GDP from indicators of structural, economic, and social development in Ukraine
<p><span>Data to estimate regression dependences of energy efficiency and environmental friendliness of GDP from indicators of structural, economic, and social development in Ukraine </span></p>
Data from: Environmental heterogeneity and not vicariant biogeographic barriers generate community wide population structure in desert adapted snakes
Genetic structure can be influenced by local adaptation to environmental heterogeneity and biogeographic barriers, resulting in discrete population clusters. Geographic distance among populations, however, can result in continuous clines of genetic divergence that appear as structured populations. Here we evaluate the relevant importance of these three factors over a landscape characterized by environmental heterogeneity and the presence of a hypothesized biogeographic barrier in producing population genetic structure within 13 codistributed snake species using a genomic dataset. We demonstrate that geographic distance and environmental heterogeneity across western North America contribute to population genomic divergence. Surprisingly, landscape features long thought to contribute to biogeographic barriers play little role in divergence community wide. Our results suggest that isolation by environment is the most important contributor to genomic divergence. Furthermore, we show that models of population clustering that incorporate spatial information consistently outperform nonspatial models, demonstrating the importance of considering geographic distances in population clustering. We argue that environmental and geographic distances as drivers of community-wide divergence should be explored before assuming the role of biogeographic barriers.
Data from: The spatial structure of phylogenetic and functional diversity in the United States and Canada: an example using the sedge family (Cyperaceae)
Systematically quantifying diversity across landscapes is necessary to understand how clade history and ecological heterogeneity contribute to the origin, distribution, and maintenance of biodiversity. Here, we chart the spatial structure of diversity among all species in the sedge family (Cyperaceae) throughout the USA and Canada. We first identify areas of remarkable species richness, phylogenetic diversity, and functional trait diversity, and highlight regions of conservation priority. We then test predictions about the spatial structure of this diversity based on the historical biogeography of the family. Incorporating a phylogeny, over 400,000 herbarium records, and a database of functional traits mined from online floras, we find that species richness and functional trait diversity peak in the Northeastern USA, while phylogenetic diversity peaks along the Gulf of Mexico. Floristic turnover among assemblages increases significantly with distance, but phylogenetic turnover is twice as rapid along latitudinal gradients as along longitudinal gradients. These patterns reflect the expected distribution of Cyperaceae, which originated in the tropics but radiated in temperate regions. We identify assemblages with an abundance of rare, range-restricted lineages, and assemblages composed of species generally lacking from diverse regions. We argue that both of these metrics are useful for developing targeted conservation strategies. We use the data generated here to establish future research priorities, including the testing of a series of hypotheses regarding the distribution of chromosome numbers, photosynthetic pathways, and resource partitioning in sedges.
Data from: Genomic signatures of paleodrainages in a freshwater fish along the southeastern coast of Brazil: genetic structure reflects past riverine properties
Past shifts in connectivity in riverine environments (for example, sea-level changes) and the properties of current drainages can act as drivers of genetic structure and demographic processes in riverine population of fishes. However, it is unclear whether the same river properties that structure variation on recent timescales will also leave similar genomic signatures that reflect paleodrainage properties. By characterizing genetic structure in a freshwater fish species (Hollandichthys multifasciatus) from a system of basins along the Atlantic coast of Brazil we test for the effects of paleodrainages caused by sea-level changes during the Pleistocene. Given that the paleodrainage properties differ along the Brazilian coast, we also evaluate whether estimated genetic diversity within paleodrainages can be explained by past riverine properties (i.e., area and number of rivers in a paleodrainage). Our results demonstrate that genetic structure between populations is not just highly concordant with paleodrainages, but that differences in the genetic diversity among paleodrainages correspond to the joint effect of differences in the area encompassed by, and the number of rivers, within a paleodrainage. Our findings extend the influence of current riverine properties on genetic diversity to those associated with past paleodrainage properties. We discuss how these findings may explain the inconsistent support for paleodrainages in structuring divergence from different global regions and the importance of taking into account past conditions for understanding the high species diversity of freshwater fish that we currently observe in the world, and especially in the Neotropics.
Data from: Structural and defensive roles of angiosperm leaf venation network reticulation across an Andes-Amazon elevation gradient
1.The network of minor veins of angiosperm leaves may include loops (reticulation). Variation in network architecture has been hypothesized to have hydraulic and also structural and defensive functions. 2.We measured venation network trait space in eight dimensions for 136 biomass-dominant angiosperm tree species along a 3,300 m elevation gradient in southeastern Peru. We then examined the relative importance of multiple ecological, and evolutionary predictors of reticulation. 3.Variation in minor venation network reticulation was constrained to three axes. These axes described branching vs. reconnecting veins, elongated vs. compact areoles, and high vs. low density veins. Variation in the first two axes was predicted by traits related to mechanical strength and secondary compounds, and in the third axis by site temperature. 4.Synthesis. Defensive and structural factors primarily explain variation in multiple axes of reticulation, with a smaller role for climate-linked hydraulic factors. These results suggest that venation network reticulation may be determined more by species interactions than by hydraulic functions.
Data from: The socially parasitic ant Polyergus mexicanus has host-associated genetic population structure and related neighboring nests
<p>The genetic structure of populations can be both a cause and a consequence of ecological interactions. For parasites, genetic structure may be a consequence of preferences for host species or of mating behavior. Conversely, genetic structure can determine where conspecific interactions among parasites lay on a spectrum from cooperation to conflict. We used microsatellite loci to characterize the genetic structure of a population of the socially parasitic dulotic (aka "slave-making") ant (<i>Polyergus mexicanus</i>), which is known for its host-specificity and conspecific aggression. First, we assessed whether the pattern of host species use by the parasite has influenced parasite population structure. We found that host species use was correlated with subpopulation structure, but this correlation was imperfect: some subpopulations used one host species exclusively, while others used several. Second, we examined the viscosity of the parasite population by measuring the relatedness of pairs of neighboring parasitic ant nests at varying distances from each other. Although natural history observations of local dispersal by queens suggested the potential for viscosity, there was no strong correlation between relatedness and distance between nests. However, 35% of nests had a closely related neighboring nest, indicating that kinship could potentially affect the nature of some interactions between nests of this social parasite. Our findings confirm that ecological forces like host species selection can shape the genetic structure of parasite populations, and that such genetic structure has the potential to influence parasite-parasite interactions in social parasites via inclusive fitness.</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.