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Figure 9 in Anatomical study of two previously undescribed specimens of Clevosaurus hudsoni (Lepidosauria: Rhynchocephalia) from Cromhall Quarry, UK, aided by computed tomography, yields additional information on the skeleton and hitherto undescribed bones
Figure 9. Photographs and surface models of Clevosaurus hudsoni specimen NHMUK PV R36832. Left dentary in (A, C) lateral and (D) medial views. B, partial left dentary in lateral view showing wear facets. E, left articular complex in dorsal view. F, left surangular in lateral view. G, left articular in dorsal view. H, right articular in lateral view.
Figure 8 in Anatomical study of two previously undescribed specimens of Clevosaurus hudsoni (Lepidosauria: Rhynchocephalia) from Cromhall Quarry, UK, aided by computed tomography, yields additional information on the skeleton and hitherto undescribed bones
Figure 8. Photograph and surface models of Clevosaurus hudsoni specimen NHMUK PV R36832. Braincase bones in (A, B) posterodorsal, (C) right lateral and (D) anteroventral views.
Figure 19 in Anatomical study of two previously undescribed specimens of Clevosaurus hudsoni (Lepidosauria: Rhynchocephalia) from Cromhall Quarry, UK, aided by computed tomography, yields additional information on the skeleton and hitherto undescribed bones
Figure 19. Photographs and surface models of Clevosaurus hudsoni specimen NHMUK PV R36846. A, distal head of broken femur in ventrolateral view. Left tibia in (B) anterior, (C) lateral and (D) posterior views. Left fibula in (E) anterior and (F) posterior views. G, astragalus, calcaneum and tarsal bones in dorsal view. H, digit i in dorsolateral view. I, digit i phalanx and ungual in dorsolateral view. Astragalus and calcaneum in (J) dorsal and (K) ventral views.
Dataset from "A Hybrid 3D Printed Hand Prosthesis Prototype Based on sEMG and a Fully Embedded Computer Vision System"
<p>Open access dataset containing objects images to be used in training computer vision systems for hand gestures recognition. There are 4 zip files with 6900 images for tripod pinch, 8345 images for palmar grasp with neutral wrist position, 8280 images for palmar grasp with pronated wrist, and 2188 images for key grasp pattern. These are images from the Newcastle Grasp Library (NGL) and the Amsterdam Object Image Library (ALOI). There are other 3 zip files with musical and computer keyboards and tablets images.</p> <p> </p>
Table A6 images from Computer-aided drug design (CADD) to de-orphanise marine molecules: Finding potential therapeutic agents for neurodegenerative and cardiovascular diseases
<p>High Reslution Images from Table A6</p>
Computational output dataset for monoterpene glycoside hydrolysis: Supplement to 10.5281/zenodo.5346588
<p>Computational data resulting from optimisation and vibrational analysis of monoterpenes, geraniol and linalool, resulting from acid-catalysed hydrolysis of geraniol glucoside. Supplementary dataset for the computation described in:</p> <p>Hixson, Josh, Pisaniello, Lisa, Parker, Mango, Grebneva, Yevgeniya, Bilogrevic, Eleanor, Stegmann, Robin, & Francis, Leigh. (2021, August 31). Methods for predicting and assessing flavour evolution during white wine ageing. https://doi.org/10.5281/zenodo.5346589</p> <p>Structures were drawn in Avogadro (version 1.2.0), then optimised (UFF) and systematic rotor conformer search performed, with the resulting geometry used to create initial input files for GAMESS (Linux distribution, version 2019 R2, University of Iowa, USA) running on the University of South Australia’s High Performance Compute Cluster. Calculations were first performed for molecules in the gas phase (RHF/3-21G) to provide starting geometries which were then used as the input for density functional theory (B3LYP/6-311G(d)) equilibrium geometry calculations in water (SMD solvent model). Local minima were confirmed by vibrational analysis and the presence of all real frequencies. Each calculation was performed in parallel across eight cores.</p> <p>The chemical structures input into Avagadro and the naming used in computational files can be found in 'starting_structures_naming.png' and the scheme of glucoside hydrolysis and rearrangement from the original manuscript has been re-published here as 'glycoside_hydrolysis_scheme.png'. Two computational output files (.log) are present for each structure: an output of the geometry optimisation ending in '_B3LYP_6311G_aq.log', and; the optimised geometry analysed by vibrational analysis, including thermochemistry, denoted with '_vibrational.log'. </p> <p>The compounds, compound file naming (starting_structures_naming.png) and structure numbering in the original work (glycoside_hydrolysis_scheme.png) are as follows: geraniol glucoside, geraniol_gluc, compound 1; protonated geraniol glucoside, geraniol_gluc_protonated, compound 2; linalyl or geranyl cation (identical structures found after geometry optimisation), linalyl_cation or geranyl cation, compound 3, protonated geraniol, geraniol_protonated, compound 4; geraniol, geraniol, compound 5; protonated linalool, linalool_protonated, compound 6; linalool, linalool, compound 7.</p> <p> </p> <p> </p>
GALA: a computational framework for de novo chromosome-by-chromosome assembly with long reads
<p>C.elegans, O.sativa and Human assemblies produced by GALA software</p>
Data from Wilson et al.: Applying computer vision to digitised natural history collections for climate change research: temperature-size responses in British butterflies
<p>This dataset supports the publication: Wilson et al. "Applying computer vision to digitised natural history collections for climate change research: temperature-size responses in British butterflies". These are the data used for the data figures (Fig 3-6, SI Figs 1-2) and the supplementary information tables.</p>
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis
<p>data files, including ML models of dynamic classifiers, trajectories of electronic structure and geometric features, optimized geometries, and final csv files.</p>
X-ray micro-computed tomography of mushrooms during the instant controlled pressure drop (DIC) combined hot air drying
<p>These videos present the microstructure evolution of the <em>shiitake </em>mushrooms during the instant controlled pressure drop (DIC) combined hot air drying as well as the comparison of the microstructure of dried mushrooms treated by different drying methods.</p> <p>Fresh-skin and fresh-lamella indicate fresh mushroom cubes including skin and lamella parts respectively.</p> <p>DIC-skin and DIC-lamella indicate DIC treated mushroom cubes including skin and lamella parts respectively.</p> <p>DIC-HA35 dried-skin, DIC-HA65 dried-skin, and HA35 dried-skin indicate mushroom cubes including skin parts that were dried by DIC combined hot air drying at 35 ℃, DIC combined hot air drying at 65 ℃ and hot air drying at 35 ℃, respectively.</p>
Computational validation of clonal and subclonal copy number alterations from bulk tumour sequencing
<p>Somatic variant identification from WGS data is a crucial step in the analysis of cancer genomes. Several tools are available to perform mutations calling, however, the noisiness of data requires appropriate quality control assessment. In the preprint work available at https://doi.org/10.1101/2021.02.13.429885 we present CNAqc, an R package devised to assess the quality of allele-specific Copy Number Alterations (CNA), somatic mutations, and tumor purity estimates. In order to test the model, we ran CNAqc on 2778 single-sample PCAWG whole-genomes and 48 TCGA whole-exomes. We uploaded the results of our analysis using the release of the tool available at https://github.com/caravagnalab/CNAqc/releases/tag/rr_22_0.1 in the form of .rds files. All the necessary details for the reproduction of our results are reported in the Supplementary Materials of the above-mentioned manuscript.</p>
Massively parallel, computationally-guided design of a pro-enzyme
<p>Confining the activity of a designed protein to a specific microenvironment would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as inactive zymogens that can be activated by proteolysis, it has been challenging to re-design any chosen enzyme to be similarly stimulus-responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for pro-enzyme design. As a model system, we employ carboxypeptidase G2 (CPG2), a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug toxicity. Detailed kinetic characterization of most effective designed variants shows that they are inhibited by approximately 80% compared to the unmodified protein, and their activity is fully restored following incubation with site-specific proteases. Introducing disulfide bonds between the pro- and catalytic domains based on the design models increases the degree of inhibition to 98%, but decreases the degree of restoration of activity by proteolysis. A selected disulfide-containing pro-enzyme exhibits significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization provides detailed insights into the pro-domain binding and inhibition mechanisms. The described methodology is general and could enable the design of a variety of pro-proteins with precise spatial regulation.</p>
Data and Codes of Characterizing Uncertainties of Earth System Modeling with Heterogeneous Many-core Architecture Computing
<p>These are the supporting information to verify the results in the paper, including input data, model outputs, the postprocessing scripts and the source codes.</p>
Optocoder: computational decoding of spatially indexed bead arrays
<p>Spatial transcriptomics technologies that can quantify gene expression in space are transforming contemporary biology research. Some of such methods use spatially barcoded bead arrays that are optically sequenced by a microscopy setup to detect bead barcodes in space which can be consecutively matched to cell barcodes from the respective single cell sequencing experiment. To have good quality barcodes and a high number of barcode matches in space, robust and efficient computational pipelines are needed to process raw microscopy images and call the bases of bead barcodes accurately. Here, we present Optocoder, a computational pipeline that takes raw optical sequencing microscopy images as input and outputs bead barcodes in space. Optocoder efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal such as crosstalk and phasing before base calling. Furthermore, we implement a machine learning pipeline that is trained using the signal from the beads that match to illumina barcodes in order to predict non-matching bead barcodes which can boost up the number of barcode matches. We benchmark Optocoder using data from an in-house spatial transcriptomics platform as well as data from the Slide-seq method and we show that it can efficiently process both datasets with minimal modification.</p> <p>Here, the datasets deposited include the following:</p> <p><strong>optocoder_data:</strong> the imaging and illumina data that are used for Optocoder runs. Folder structure is as following:</p> <ol> <li><strong>imaging:</strong> the images acquired via a two laser microscopy setup during the optical sequencing process . There are four pucks (P1, P2, P3, P4) and for every puck there are 12 images where every image corresponds to one cycle of optical sequencing. Every image is a 6-channel TIFF image.</li> <li><strong>illumina: </strong>cell barcodes from library sequencing that are used for the matching</li> <li><strong>external: </strong>bead optical barcodes for the Slide-Seq and Slide-SeqV2</li> </ol> <p><strong>optocoder_v0.1.1_output: </strong>these are the output files from Optocoder runs for both in-house and Slide-Seq samples , and are used to generate the figures in the publication. Scripts to generate the figures are deposited here: https://github.com/rajewsky-lab/optocoder_scripts</p> <p><strong>run1_optocoder_v0.1.1_config_files: </strong>example config files for the optocoder run files.</p> <p> </p>
Computational dataset for the manuscript "Tethered agonist exposure in intact adhesion/class B2 GPCRs through intrinsic structural flexibility of the GAIN domain"
<p>This repository provides url links to the MDsrv sessions for the manuscript: <em>Tethered agonist exposure in intact adhesion/class B2 GPCRs through intrinsic structural flexibility of the GAIN domain<strong>.</strong></em> </p> <p><strong>Link 1</strong>: L1 dynamic: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1.ngl </a></p> <p><strong>Link 2</strong>: G1 dynamic: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/G1.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/G1.ngl</a></p> <p><strong>Link 3</strong>: E5 static: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5_crevice.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5_crevice.ngl</a></p> <p><strong>Link 4: </strong>E5 dynamic: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5.ngl</a></p> <p><strong>Link 5: </strong>E5 +3 static: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5+3.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5+3.ngl</a></p> <p><strong>Link 6: </strong>E5 +6 static: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5+6.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E5+6.ngl</a></p> <p><strong>Link 7: </strong>E2 dynamic: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E2.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/E2.ngl</a></p> <p><strong>Link 8: </strong>L1 Phe+3Lys dynamic: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1Phe+3Lys.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1Phe+3Lys.ngl</a></p> <p><strong>Link 9: </strong>L1 Leu+6Lys dynamic: <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1Leu+6Lys.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1Leu+6Lys.ngl</a></p> <p><strong>Link 10: </strong>L1 dynamic (ribbon representation): <a href="http://proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1Ribbon.ngl">proteinformatics.uni-leipzig.de/html/mdsrv.html?load=file://base/aGPCRs/L1Ribbon.ngl</a></p> <p> </p> <p> </p>
Raw Experimental Data of the Master's Thesis: Improving Serverless Edge Computing for Network Bound Workloads
<p>Raw Experimental Data of the Master's Thesis: Improving Serverless Edge Computing for Network Bound Workloads</p> <p>Please see the README for information on parsing and data structure.<br> Some of the data might need additional explanations. In case of confusion don't hesitate to contact me under jacob.palecek@outlook.com</p>
UAS dataset for Crop Water Stress Index computation and Triangle Method applications
<p>This dataset is related with a field campaigns carried out on a tangerine field located near Palermo (Sicily), within the Harmonious COST action CA16219 - Harmonization of UAS techniques for agricultural and natural ecosystems monitoring-, activities framework. The general aim was to acquire UAS (Unmanned Aerial Systems) remotely sensed imagery to detect the vegetation stress status. A multispectral camera (RIKOLA) and a thermal one (FLIR) were used. The images are already georeferenced with 3.7 cm pixel size. The dataset could be used to compute the Crop Water Stress Index and to compute the moisture status of the field by means of a combined use of the optical and thermal images. The dataset includes meteo data registered by a meteo station nearby the site.</p>
Supplementary Data for 'Gas-phase Peroxyl Radical Recombination Reactions: A Computational Study of Formation and Decomposition of Tetroxides'
<p>This dataset contains supplementary data for the publication 'Gas-phase Peroxyl Radical Recombination Reactions: A Computational Study of Formation and Decomposition of Tetroxides. Data consist of various output-files of quantum chemical computations.</p>
Osteolitic vs Osteoblastic metastatic lesion: Computational modeling of fracture risk in the human vertebra after screws fixation procedure
<p>Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screwfixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing the surgical treatment. This work proposes an image-basedfinite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for the metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response, and suggest better account these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for irregular shape of the overall metastatic tissue has a not significant effect on fracture load of vertebra macroscopically. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining the fracture risk. The proposed computational approach moves towards defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.</p>
Data from: Computational Modeling of Gluteus Medius Muscle Moment Arm in Caviomorph Rodents Reveals Ecomorphological Specializations
<p>The data stored in this repository allow the reproduction of the study described in the following. Vertebrate musculoskeletal locomotion is realized through lever-arm systems. The instantaneous muscle moment arm (IMMA), which is expected to be under selective pressure and thus of interest for ecomorphological studies, is a key aspect of these systems. The IMMA changes with joint motion and its length change is technically difficult to acquire—usually, proxies such as osteological in-levers are used instead—and has not been compared in a larger phylogenetic ecomorphology framework, yet. We used 18 species of the ecologically diverse clade of caviomorph rodents to test whether its diversity is reflected in the IMMA of the hip extensor M. gluteus medius. A large IMMA is beneficial for torque generation; a small IMMA facilitates fast joint excursion. We expected large IMMAs in scansorial species, small IMMAs in fossorial species, and somewhat intermediate IMMAs in cursorial species, depending on the relative importance of acceleration and joint angular velocity. We modelled the IMMA over the entire range of possible hip extensions and applied macroevolutionary model comparison to selected joint poses. We also obtained the osteological in-lever of the M. gluteus medius to compare it to the IMMA. At small hip extension, the IMMA was largest on average in scansorial species, while the other two lifestyles were similar. We interpret this as an emphasized need for increased hip joint torque when climbing on inclines, especially in a crouched posture. Cursorial species might benefit from a fast joint excursion, but their similarity with the fossorial species is difficult to interpret and could hint at ecological similarities. At larger extension angles, cursorial species displayed the second-largest IMMAs after scansorial species. The larger IMMA optimum results in powerful hip extension which coincides with forward acceleration at late stance beneficial for climbing, jumping, and escaping predators. This might be less relevant for a fossorial lifestyle. The results of the in-lever only matched the IMMA results of larger hip extension angles, suggesting that the modelling of the IMMA provides more nuanced insights into adaptations of musculoskeletal lever arm systems than this osteological proxy.</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.