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ShareScore release 0.9.0
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261 results for “protein prediction”
Common protein interactions explain variant oncofusion function and predict a novel oncofusion in rhabdomyosarcoma
<p>Original Westerns from publications</p>
A Folding–Docking–Affinity framework for protein–ligand binding affinity prediction
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Dataset for the paper: Predicting protein functions using positive-unlabeled ranking with ontology-based priors
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Predicting Protein Synergistic Effect in Arabidopsis using Epigenome Profiling (Data Source)
<p>Peak-calling data of QHistone Histone related 1,534 ChIP-seqs and protein 1,566 ChIP-seqs.</p> <p><strong>histone related chip seq:</strong> The folder contains bed file (narrowPeak) of 1,534 histone ChIP-seqs and corrosponding meta-data.</p> <p><strong>protein chip seqs: </strong>The folder contains bed file (narrowPeak) of 1,566 protein ChIP-seqs and corrosponding meta-data.</p>
A joint embedding of protein sequence and structure enables robust variant effect predictions
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MechRNA: prediction of lncRNA mechanisms from RNA-RNA and RNA-protein interactions
<p>Supplementary Data</p>
Sequence data and structural data utilized in the study and analysis of grain protein function prediction.
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Conformation Database for Publication: Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction
<p><strong>Conformation database</strong> for 2022 Publication "Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction"</p> <ul> <li>DOI of Physica A publication: <a href="https://doi.org/10.1016/j.physa.2022.128395">https://doi.org/10.1016/j.physa.2022.128395</a></li> <li>GitHub source code: <a href="https://github.com/CompSoftMatterBiophysics-CityU-HK/Applying-DRL-to-HP-Model-for-Protein-Structure-Prediction">https://github.com/CompSoftMatterBiophysics-CityU-HK/Applying-DRL-to-HP-Model-for-Protein-Structure-Prediction</a></li> </ul> <p>This conformation database shows the distinct conformations of best-known and next best energies:</p> <p>├── <strong>20merA</strong><br> │ ├── <strong>20merA_E8_set</strong><br> │ ├── <strong>20merA_E9_set</strong><br> │ ├── confs_20merA_E8.txt<br> │ └── confs_20merA_E9.txt<br> ├── <strong>20merB</strong><br> │ ├── <strong>20merB_E10_set</strong><br> │ ├── <strong>20merB_E9_set</strong><br> │ ├── confs_20merB_E10.txt<br> │ └── confs_20merB_E9.txt<br> ├── <strong>24mer</strong><br> │ ├── <strong>24mer_E8_set</strong><br> │ ├── <strong>24mer_E9_set</strong><br> │ ├── confs_24mer_E8.txt<br> │ └── confs_24mer_E9.txt<br> ├── <strong>25mer</strong><br> │ ├── <strong>25mer_E7_set</strong><br> │ ├── <strong>25mer_E8_set</strong><br> │ ├── confs_25mer_E7.txt<br> │ └── confs_25mer_E8.txt<br> ├── <strong>36mer</strong><br> │ ├── <strong>36mer_E13_set</strong><br> │ ├── <strong>36mer_E14_set</strong><br> │ ├── confs_36mer_E13.txt<br> │ └── confs_36mer_E14.txt<br> ├── <strong>48mer</strong><br> │ ├── <strong>48mer_E22_set</strong><br> │ ├── <strong>48mer_E23_set</strong><br> │ ├── confs_48mer_E22.txt<br> │ └── confs_48mer_E23.txt<br> └── <strong>50mer</strong><br> ├── <strong>50mer_E20_set</strong><br> ├── <strong>50mer_E21_set</strong><br> ├── confs_50mer_E20.txt<br> └── confs_50mer_E21.txt</p>
Mapping Synthetic Binding Proteins Epitopes on Diverse Protein Targets by Protein Structure Prediction and Protein-Protein Docking
<p>The predicted 3D structures of 145 SBPs and the 96 models of SBPs in complex with protein targets.</p>
Functional prediction of select proteins from the gut archaeome
<p>Synteny plots of archaeal gut-specific unique and homologous gene clusters. </p>
PDBscreen with multiple data augmentation strategies suitable for training protein-ligand interaction prediction methods
<p>PDBscreen with multiple data augmentation strategies suitable for training protein-ligand interaction prediction methods.</p> <p>PDBscreen is the training dataset for EquiScore.</p>
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing
<p>Data set provided with the paper "HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing". Please solely cite the <a href="https://openreview.net/forum?id=YDJRFWBMNby&noteId=vl18g7_lVT">paper</a> if you use the data.</p> <p>Data was downloaded from the provided <a href="https://github.com/VITA-Group/HotProtein">GitHub</a> links 2023/07/11:</p> <p>Datasets</p> <ul> <li>HP-S2C2</li> <li>HP-S2C5</li> <li>HP-S:</li> </ul>
Data for CASP15 performance benchmarking of the state-of-the-art protein structure prediction methods
<p>CASP15 performance benchmarking of the state-of-the-art protein structure prediction methods</p>
Genomically predicted theoretical protein mass database for mass spectrometry (GPMsDB) R01-RS95
<p>GPMsDB-tk/GPMsDB-dbtk are software toolkits for assigning taxonomic identification to user-provided MALDI-TOF mass spectrometry profiles obtained from bacterial and archaeal cultured isolates. This is a database (release R01-RS95) used for the toolkits. This database is released under the <a href="https://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.</p> <p>GPMsDB-tk/GPMsDB-dbtk are available at <a href="https://github.com/ysekig">https://github.com/ysekig</a>. Details are shown at the GitHub sites.</p>
GcForest-based Compound-Protein Interaction Prediction Model and Its Application in Discovering Small-Molecule Drugs Targeting CD47
<p><strong>This is a file of all raw data and processed data concerned in the article "GcForest-based Compound-Protein Interaction Prediction Model and Its Application in Discovering Small-Molecule Drugs Targeting CD47", this file contain 6 sub-files, namely GCVec——humans, GCVec——celegans, GCVec——challenging dataset, GCVec——latest BindingDB, GCVec——known CD47 inhibitors, GCVec——specs, respectively, fully cover all parts of the article.</strong></p>
Aurinia Early Urinary Protein Reduction Predicts Response
ClinicalTrials.gov study NCT02949973. IPD Sharing: NO. Countries: 1. Publications: 0.
Combination of Serum Measurements of Molecular Biomarkers and Serum Protein Profiling Can be Used to Predict Which Patients Undergoing Prostatic Biopsy Will be Diagnosed With Cancer
ClinicalTrials.gov study NCT00773773. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of Serum Levels of C Reactive Protein (CRP) and Its Correlation With Fetal Ultrasound Parameters in the Prediction of Threatened Miscarriage in the First Trimester
ClinicalTrials.gov study NCT06011057. IPD Sharing: NO. Countries: 1. Publications: 0.
Automated protein-protein structure prediction of the T cell receptor-peptide major histocompatibility complex
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Data from: Protein pheromone expression levels predict and respond to the formation of social dominance networks
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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.