بدائل البحث:
protein classification » protein quantification (توسيع البحث), emotion classification (توسيع البحث), improved classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
complex protein » complex process (توسيع البحث), complex patterns (توسيع البحث), complex problems (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
protein classification » protein quantification (توسيع البحث), emotion classification (توسيع البحث), improved classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
complex protein » complex process (توسيع البحث), complex patterns (توسيع البحث), complex problems (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
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41
Table1_Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.XLSX
منشور في 2023"…</p><p>Methods: In this study, based on the deep learning models that implement pixel-level binary classification prediction in computer vision, we viewed the CircRNA-protein binding sites prediction as a nucleotide-level binary classification task, and use a fully convolutional neural networks to identify CircRNA-protein binding motif sites (CPBFCN).…"
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42
DataSheet1_Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network.PDF
منشور في 2023"…</p><p>Methods: In this study, based on the deep learning models that implement pixel-level binary classification prediction in computer vision, we viewed the CircRNA-protein binding sites prediction as a nucleotide-level binary classification task, and use a fully convolutional neural networks to identify CircRNA-protein binding motif sites (CPBFCN).…"
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43
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Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
منشور في 2025"…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …"
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45
Models and Dataset
منشور في 2025"…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …"
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46
Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
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47
Structure-based antibody paratope prediction with 3D Zernike descriptors and SVM
منشور في 2019"…<br><b><br>test_set_protein_ag_structures_descriptors.tar.gz - </b>Contains the PDB structures of the antibody-antigen complexes in the test set of antibodies complexed with protein antigens; the 3D Zernike Descriptors for each antibody; the predicted patch scores for each antibody; other supplementary files. …"
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48
Flow diagram of the automatic animal detection and background reconstruction.
منشور في 2020"…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …"
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49
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"