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.
266
datasets available to search
ShareScore release 0.9.0
Dataset results
266 results for “Protein Modelling”
Protein Subcellular localization prediction data used in the article entitled "MSclassifier: Median-Supplement model-based Classification tool for automated knowledge discovery"
<p>This repository contains data used to obtain results from a 5-fold cross-validation testing of how MSclassifier and other packages accurately predict protein subcellular localization in the software article entitled "MSclassifier: median-supplement model-based classification tool for automated knowledge discovery." The data used in the software article is derived from data generated in "G. K. Acquaah-Mensah, S. M. Leach, and C. Guda, Predicting the subcellular localization of human proteins using machine learning and exploratory data analysis, Genomics Proteomics Bioinformatics, 4(2):120-133, 2006, <a href="https://doi.org/10.1016/S1672-0229(06)60023-5">https://doi.org/10.1016/S1672-0229(06)60023-5</a>"</p>
Data from: Oncogene inference optimization using constraint-based modelling incorporated with protein expression in normal and tumour tissues
Cancer cells are known to exhibit unusual metabolic activity and yet, few metabolic cancer driver genes are known. Genetic alterations and epigenetic modi cations of cancer cells result in the abnormal regulation of cellular metabolic pathways that are different when compared to normal cells. Such a metabolic reprogramming can be simulated using constraint-based modelling approaches towards predicting oncogenes. We introduced the tri-level optimization problem to use the metabolic reprogramming towards inferring oncogenes. The algorithm incorporated Recon 2.2 network with the Human Protein Atlas to reconstruct genome-scale metabolic network models of the tissue-speci fic cells at normal and cancer states, respectively. Such reconstructed models were applied to build the templates of the metabolic reprogramming between normal and cancer cell metabolism. The inference optimization problem was formulated to use the templates as a measure towards predicting oncogenes. The nested hybrid differential evolution algorithm was applied to solve the problem to overcome solving difficulty for transferring the inner optimization problem into the single one. Head and neck squamous cells were applied as a case study to evaluate the algorithm. We detected 13 of the top ranked one-hit dysregulations and 17 of the top ranked two-hit oncogenes with high similarity ratios to the templates. According literature survey, most inferred oncogenes are consistent with the observation in various tissues. Furthermore, the inferred oncogenes were highly connected with the TP53/AKT/IGF/MTOR signalling pathway through PTEN, which is one of the most frequently detected tumour suppressor genes in human cancer.
Serum levels of tau protein increase according to the severity of the injury in DAI rat model
<p><span><span><span><span><span><span><span><span><span><span><span>Traumatic brain injury (TBI) in the form of diffuse axonal injury (DAI) is difficult to diagnose in the early phase of the injury. Early diagnosis of DAI may provide opportunity for developing treatment and management strategies. Tau protein has been demonstrated to increase in the early phase of TBI with high diagnostic accuracy in patients with DAI. We tested the biological plausibility of tau protein using a rat DAI model by evaluating the association between serum tau levels and the severity of brain injury. DAI was induced in animals using the Marmarou model. After a survival of 60 minutes, rats were anesthetized and sacrificed after obtaining blood samples (5ml) from the heart. Eighteen rats were employed in the present study and were randomly subjected to sham-operated control (n=4), mild DAI (n=7), and severe DAI (n=7). Of seven severe DAI rats, two rats that had focal injury caused by skull fracture were excluded in the measurement of tau protein level. The serum levels of tau protein in the rat DAI model were found to increase significantly and consistently according to the severity of the injury. Rats with DAI showed significantly higher serum levels of tau protein compared to sham rats; the severe DAI rats had higher levels of tau than moderate DAI and sham rats (sham vs. mild, <i>P</i>=0.02; mild vs. severe, <i>P</i>=0.02). In conclusion, serum tau protein levels may be useful as a biomarker for diagnosing and estimating the severity of DAI in the early phase.</span></span></span></span></span></span></span></span></span></span></span></p> <div> </div>
Data from: Cost of reproduction in the Queensland fruit fly: Y-model vs. lethal protein hypothesis
The trade-off between lifespan and reproduction is commonly explained by differential allocation of limited resources. Recent research has shown that the ratio of protein to carbohydrate (P:C) of a fly's diet mediates the lifespan/reproduction trade-off, with higher P:C diets increasing egg production but decreasing lifespan. To test if this P:C effect is due to changing allocation strategies (Y-model hypothesis) or detrimental effects of protein ingestion on lifespan (lethal protein hypothesis), we measured lifespan and egg production in Queensland fruit flies varying in reproductive status (mated, virgin, and sterilized females, virgin males) that were fed one of 18 diets varying in protein and carbohydrate amounts. The Y-model predicts that for sterilized females and for males, which require little protein for reproduction, there will be no effect of P:C ratio on lifespan; the lethal protein hypothesis predicts that the effect of P:C ratio should be similar in all groups. In support of the lethal protein hypothesis, and counter to the Y model, the P:C ratio of the ingested diets had similar effects for all groups. We conclude that the trade-off between lifespan and reproduction is mediated by the detrimental side-effects of protein ingestion on lifespan.
Integration of protein and coding sequences enables mutual augmentation of the language model
<p><strong>The file structure is as follows:</strong></p> <p>Project Root<br>├── TE_MRL<br>│ ├── MRL_dataset.zip<br>│ └── TE_dataset.zip<br>│<br>├── finetuned_model<br>│ ├── FoldP<br>│ ├── LocP<br>│ ├── SSP<br>│ └── SolP<br>│<br>├── tax_tsne<br>│ └── emb_3models.zip<br>│<br>└── training_data<br> ├── FoldP.csv<br> ├── LocP.csv<br> ├── SolP.csv<br> ├── SSP.pkl<br> └── pretrain_source_GCF.txt</p>
Dataset for Ha and Aylward 'Automated classification of giant virus genomes using a random forest model built on trademark protein families'
<ul><li>Genome sets used for model training and testing</li><li>Custom Python script that generated fragmented genomes at random completeness levels</li></ul>
DynamicBind: Predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model.
<p>test and training data.</p>
Datasets associated with the manuscript Protein Condensate Atlas from predictive models of heteromolecular condensate composition
<p>Datasets associated with the manuscript "Protein Condensate Atlas from predictive models of heteromolecular condensate composition".</p>
Source data for manuscript(De novo protein design with a denoising diffusion network independent of pre-trained structure prediction models)
<p>This respository contains the source data for figure and supplementary figure in manuscript(SCUBA-D).</p>
Source data for manuscript(De novo protein design with a denoising diffusion network independent of pre-trained structure prediction models)
<p>This respository contains the source data for figure and supplementary figure in manuscript(SCUBA-D).</p>
Data for DualNetGO: A Dual Network Model for Protein Function Prediction via Effective Feature Selection
<p>Data used in the paper, including annotation files, graph embeddings from TransformerAE, and protein attributes for both human and mouse, and for cafa3 data. Extract and place them in the <em>data </em>folder.</p>
Time-series analysis of rhenium(I) organometallic covalent binding to a model protein for drug development: Raw Diffraction Images (38 week soak). Zenodo
<p>The synchrotron raw diffraction images obtained at 38 weeks and wavelength 0.976 Å, illustrates the covalent coordination of the rhenium(I) tricarbonyl fragment to the His and Asp amino acid residues as well as movement along the solvent channels as described in the publication titled "Time-series analysis of rhenium(I) organometallic covalent binding to a model protein for drug development", written by Jacobs, Helliwell & Brink,<em> IUCrJ</em>, 2024, https://doi.org/10.1107/S2052252524002598.</p> <p>The raw diffraction images for the DLS data sets are made available at the Zenodo research data archive, as specified in the publication.</p>
Sampled Structures from Diffusion Models for Protein SHAPES
<p>Data associated with SHAPES (Structural and Hierarchical Assessment of Proteins with Embedding Similarity)</p> <ul> <li><code>rmsd.tar.gz</code> : RMSD and TM scores of ESMFold predicted structures with original designed backbones.</li> <li><code>mpnn.tar.gz</code> : ProteinMPNN designed sequences.</li> <li><code>raster.tar.gz</code> : CATH and sampled structures annotated with the grid square label after rasterization. Also includes the specific structures which are displayed in the raster plots.</li> <li><code>dssp.tar.gz</code> : Secondary structure frequences computed by DSSP.</li> <li><code>samples.tar.gz</code> : All sampled structures.</li> </ul> <p>Due to size, the ESMFold predicted structures for eight ProteinMPNN-designed sequences per sampled backbone are not included.</p> <p> </p> <p>Code: <code>proteinshapes-main.zip</code></p>
i-Tasser 3D Strucutres of Blood Plasma Proteins for United Atom Multiscale Modelling Of Bio-Nano Interactions
<p>3D Structures of blood plasma proteins as per proteomic data on protein corona for AgNPs presented in this publication:</p> <blockquote> <p>Gorshkov V, Bubis JA, Solovyeva EM, Gorshkov M, KjeldsenF. Protein corona formed on silver nanoparticles in blood plasma is highly selective and resistant to physicochemical changes of the solution. Environ. Sci.: Nano, 2019,6, 1089-1098. doi: 10.1039/C8EN01054D</p> </blockquote> <p>Note, that the dataset is different from the one used in this publication:</p> <blockquote> <p>Alsharif SA, Power D, Rouse I, Lobaskin V. In Silico Prediction of Protein Adsorption Energy on Titanium Dioxide and Gold Nanoparticles. Nanomaterials (Basel). 2020 Oct 4;10(10):1967. doi: 10.3390/nano10101967.</p> </blockquote> <p>Files were prepared with I-TASSER utility:</p> <blockquote> <p>J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure and function prediction. Nature Methods, 12: 7-8 (2015).</p> </blockquote> <p> </p>
i-Tasser 3D Strucutres of Milk Proteins for United Atom Multiscale Modelling Of Bio-Nano Interactions
<p>The list of milk proteins was obtained from this work:</p> <blockquote> <p>Tacoma R, Fields J, Ebenstein DB, Lam YW, Greenwood SL. Characterization of the bovine milk proteome in early-lactation Holstein and Jersey breeds of dairy cows. Journal of Proteomics, 2016 (130), 200-210.</p> </blockquote> <p>Files were prepared with I-TASSER utility:</p> <blockquote> <p>J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure and function prediction. Nature Methods, 12: 7-8 (2015).</p> </blockquote>
Results for Genome scale modeling of the protein secretory pathway reveals novel targets for improved recombinant protein production in yeast
<p>This dataset contains the original results for the paper "Genome scale modeling of the protein secretory pathway reveals novel targets for improved recombinant protein production in yeast". To reproduce all figures in this paper, this dataset is required. The scripts can be found in Github (https://github.com/SysBioChalmers/pcSecYeast)</p>
Modeling of protein conformational changes with Rosetta guided by limited experimental data
<p>Demos, models and files needed to reproduce results of the paper in the title</p>
Word folder for images in research paper titled "INSILICO MODELING OF BLADDER CANCER ASSOCIATED PROTEIN"
<p>Bladder cancer is one of several types of cancer arising from the tissues of the urinary bladder. It is a disease in which cells grow abnormally and have the potential to spread to other parts of the body. In the study a<span> 3D model was obtained using multiple templates. </span>The stereo chemical quality of the model was assessed using RAMACHANDRAN PLOT analysis. The attached word file contains the images and plots pertaining to this study.</p> <p> </p> <p> </p>
Molecular models of A501X variants of penicillin-binding protein PBP2
<p>Each archive comprices a set of PDB and PSF files for PBP2 and its A501V, A501P and A501R variants.</p> <p><a href="../api/records/11660179/draft/files/QMMM_MD_models.7z/content" target="_blank" rel="noopener">QMMM_MD_models.7z</a> –QMMM_MD_models.7z full-atom models for molecular dynamic simulations with periodic boundary conditions including QM/MM MD.</p> <p>MD_clusters.7z – representative frames from classical MD trajectories. Of particular importance is conformation of β<sub>3</sub>-β<sub>4</sub> loop (residues 498-514).</p> <p> </p>
3D full atom models of A501X variants of the penicillin-binding protein 2 with ceftriaxone
<p>The archives containPDB structures.</p> <p> <br>b3-b4-loop-representative-states.7z -- representative states obtained in MD trajectories of A501X variants of the PBP2</p> <p>The rest archves, A501X.7z contain representative frames from QM/MM MD trajectories in the stationary point regions (ES, TS1, I1, TS2, EP). Both QM part only and full-atom rectangular periodic systems are presented.</p> <p> </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.