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53 results for “Structure Discovery”
Data from: Familiarity affects social network structure and discovery of prey patch locations in foraging stickleback shoals
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Systematic Discovery of Structural Elements Governing Mammalian mRNA Stability
GEO Series GSE35800. Homo sapiens. 43 samples. Type: Non-coding RNA profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Structure-Based Discovery of Potent WD Repeat Domain 5 Inhibitors that Demonstrate Efficacy and Safety in Preclinical Animal Models
GEO Series GSE203101. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Computational discovery of conserved RNA structures and functional characterization of a structured lncRNA in Leishmania braziliensis
GEO Series GSE287035. Leishmania braziliensis. 21 samples. Type: Expression profiling by high throughput sequencing.
Unravelling WRN helicase: Structural Insights Reveal Conformational States and Opportunities for MSI-H Cancer Drug Discovery
GEO Series GSE314786. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Data for "Machine Learning Scoring Functions for Drug Discovery from Experimental and Computer-generated Protein-Ligand Structures: Towards Per-target Scoring Functions"
<p>Data used in "<em>Machine Learning Scoring Functions for Drug Discovery from Experimental and Computer-generated Protein-Ligand Structures: Towards Per-target Scoring Functions</em>"<br> by F. Pellicani, D. Dal Ben, A. Perali, S. Pilati</p> <p>If you use these data or the python script for your research or other activities, please cite the corresponding journal article.</p> <p> </p> <p>====================</p> <p>Uncompressing the zipped file <em>DataSFUnicam.zip</em> provies the following files and folders:</p> <p><br> <strong>DataSFUnicam/</strong></p> <p> </p> <p> ExperimentalDataPDBFiles/<br> <em>This folder contains 2408 .pdb files of experimental complex structures. The files are named with a univocal code corresponding to the protein-ligand complex.</em></p> <p> </p> <p> ExperimentalDataXLSXFile.xlsx<br> <em>This Excel file reports the experimental protein-ligand chemical information. In the sheet named “Foglio1”, the first column contains the univocal code of the protein-ligand complex, the second column contains the experimentally measured pK_d.</em></p> <p> </p> <p> SyntheticDataPDBFiles/<br> <em>This folder contains the .pdb files of the synthetic complex structures. The .pdb files are grouped in 17 folders according to just as many target proteins. The folders are named after the corresponding protein. Each folder contains the .pdb files for the best position of each protein-ligand pair according to the MOE docking score. The files are named with a univocal code.</em></p> <p> </p> <p> SyntheticDataXLSXFiles/<br> <em> The folder contains 17 Excel files with the chemical information of the synthetic protein-ligand complexes. The files are named after the corresponding target protein. In the sheet named “Foglio1” of each .xlsx file, the first column contains a univocal code of the protein-ligand complex in each conformation, the second column contains an auxiliary numerical code corresponding to the protein-ligand pair, the third column contains the experimentally measured pK_i, and the fourth column contains the docking score provided by the MOE software.</em></p> <p>====================</p> <p>USER GUIDE FOR THE PYTHON SCRIPT</p> <p>Download and uncompress the zipped file "<em>SFUnicam.zip</em>" with a command like "<em>unzip SFUnicam.zip</em>". </p> <p>The following file structure is created:</p> <p><em>SFUnicam/</em></p> <p> <em>ComplexToBePredictedFolder/4ey5_30.pdb <br> MaxAssMatrix.npy<br> my_model<br> devStndSynt.npy<br> mediaSynt.npy<br> UnicamSF13prot.py<br> README.txt</em><br> <br> The subfolder "<em>ComplexToBePredictedFolder/</em>" contains the example PDB file "<em>4ey5_30.pdb</em>".</p> <p>-) To execute the script "<em>UnicamSF13prot.py</em>", Python 3 should be installed with the following libraries and sublibraries:<br> <em>Keras:<br> Regularizers<br> Sequential (keras.models)<br> Conv1D, Dense, MaxPooling1D, GlobalMaxPooling1D, GlobalAveragePooling1D, AveragePooling1D (keras.layers)<br> Adam (keras.optimizers)<br> Numpy</em><br> <em>Tensorflow</em></p> <p>Operation:<br> -) Copy the .pdb file related to the protein-ligand complex whose affinity is to be predicted in the subfolder “<em>ComplexToBePredictedFolder/</em>”.<br> -) Make sure the following files are in the same folder where the python script is:<br> <em>MaxAssMatrix.npy<br> mediaSynt.npy<br> devStndSynt.npy<br> my_model</em><br> -) Run the code using Python 3 with a command like "<em>python3.x UnicamSF13prot.py</em>".<br> -) Enter the name of the protein-ligand PDB file whose affinity is to be predicted (excluding the extension ".pdb").<br> -) Read the predicted affinity from screen.<br> </p> <p> </p>
Discovery and Validation of Protein Structural Complexes in Circulating Biofluids As Novel Biomarkers for Early Diagnosis, Prognosis and Therapeutic Management of Patients Affected by Neurodegenerativ
ClinicalTrials.gov study NCT06803784. IPD Sharing: NO. Countries: 1. Publications: 0.
Discovery of pre-mRNA structural scaffold as a contributor to mammalian splicing code [In Vivo]
GEO Series GSE173177. Human adenovirus 2. 9 samples. Type: Other.
Discovery of pre-mRNA structural scaffold as a contributor to mammalian splicing code
GEO Series GSE173178. Human adenovirus 2. 59 samples. Type: Other.
SHAPE-guided RNA structure homology search and motif discovery
GEO Series GSE189259. Severe acute respiratory syndrome-related coronavirus; Severe acute respiratory syndrome coronavirus 2. 4 samples. Type: Other.
Discovery of a pre-mRNA structural scaffold as a contributor to the mammalian splicing code [in vitro]
GEO Series GSE173175. Human adenovirus 2. 50 samples. Type: Other.
Dataset related to publication: Discovery of Human Constitutive androstane receptor (CAR) agonists with imidazo[1,2-a]pyridine structure
<p>MD simulation data related to the publication Ivana Mejdrová et al.:Discovery of Human Constitutive androstane receptor (CAR) agonists with imidazo[1,2-a]pyridine structure</p> <p>Individual .zip files contain raw-desmond trajectories (trj. zip files)</p> <p>individual raw-data.zip files corresponde to the trajectory analysis.</p> <p>5us_XVP_619 corresponding name in the manuscript is ; 5us_XVP_37</p> <p>5us_XVP_676 corresponding name in the manuscript is ; 5us_XVP_39</p> <p>5us_XVP_693 corresponding name in the manuscript is ; 5us_XVP_40</p> <p>5us_XVP_763 corresponding name in the manuscript is ; 5us_XVP_48</p> <p>5us_XVP_CIT corresponding name in the manuscript is ; 5us_XVP_CITCO</p> <p> </p> <p> </p>
Fig. 5 in HSQC-based small molecule accurate recognition technology discovery of diverse cytotoxic sesquiterpenoids from Elephantopus tomentosus L. and structural revision of molephantins A and B
Fig. 5. The ORTEP drawing of 1, 4, 6, 7 and 15.
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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.