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46 results for “Scoring function”
Accuracy or novelty: what can we gain from target-specific machine learning-based scoring functions in virtual screening?
<p>Datasets, features, and some representative scripts utilized in the paper "Accuracy or novelty: what can we gain from target-specific machine learning-based scoring functions in virtual screening?" </p>
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>
Validation of the ICH Score for the Prediction of 12-month Functional Outcome in Patients With Primary Intracerebral Hemorrhage
ClinicalTrials.gov study NCT05808777. IPD Sharing: NO. Countries: 1. Publications: 0.
A 12 Months Prospective Study Comparing Functional Outcome Scores in Hip Arthroscopic Labral Repair Versus Debridement
ClinicalTrials.gov study NCT06288867. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effect of TAP Block on GI Function After Sleeve Gastrectomy Using PRO-diGI Scale and Perlas Score
ClinicalTrials.gov study NCT07168538. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Dexamethasone, Dexmedetomidine and Their Combination on Post op. GIT Function Measured by I-FFED Score Post Laparoscopic Cholecystectomy
ClinicalTrials.gov study NCT07329933. IPD Sharing: NO. Countries: 1. Publications: 0.
Simple Knee Value, a Simple Score for Functional Assessment of the Knee
ClinicalTrials.gov study NCT04653272. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparison of the Speed of Functional Recovery (Constant Score) Between Two Different Approaches of Humeral Nailing in Humeral Fractures: Through the Rotator Cuff or Through the Rotator Interval Split
ClinicalTrials.gov study NCT04917536. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Prognostic Outcome Score in Functional Neurological Disorders
ClinicalTrials.gov study NCT05003557. IPD Sharing: NO. Countries: 1. Publications: 0.
Impact of Time on Sexual Function (FSFI® Score) After Hysterectomy
ClinicalTrials.gov study NCT05728281. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Adaptation of a Premorbid Function Scoring System as a Predictor for Intensive Care Unit Mortality
ClinicalTrials.gov study NCT02386254. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effectiveness of Cingal™ for Improving Pain Scores and Function in Anterior Knee Pain
ClinicalTrials.gov study NCT05714397. IPD Sharing: NO. Countries: 1. Publications: 0.
Psychometric Validation of the Hemophilia Functional Ability Scoring Tool (Hemo-FAST)
ClinicalTrials.gov study NCT04731701. IPD Sharing: NO. Countries: 1. Publications: 0.
Predicting Postoperative Ambulation Following Selective Dorsal Rhizotomy Based on Preoperative Gross Motor Function Score
ClinicalTrials.gov study NCT06610370. IPD Sharing: NO. Countries: 1. Publications: 0.
Changes in Functional Movement Scores Associated With Multimodal Chiropractic Care: a Pilot Feasibility Study
ClinicalTrials.gov study NCT05690568. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Validity and Reliability of the Turkish Version of the Functional Shoulder Score
ClinicalTrials.gov study NCT03658707. IPD Sharing: NO. Countries: 1. Publications: 0.
Effects of Proximal and Distal Tibiofibular Joint Manipulation on Lower Extremity Muscle Activation, Ankle Range of Motion, and Functional Outcome Scores in Individuals With Chronic Ankle Instability
ClinicalTrials.gov study NCT00601471. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Construction of a Multidimensional Score for the Functional Prognosis of Cerebral Infarctions
ClinicalTrials.gov study NCT04802772. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Average ANKLE GO Score in the Objective Functional Assessment of the Ankle in Healthy Military Personnel (ANKMIL)
ClinicalTrials.gov study NCT07344493. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Patient Scores and Functional Tests After Hip Surgery
ClinicalTrials.gov study NCT07048041. IPD Sharing: NO. Countries: 1. Publications: 0.
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