Category: protein
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SPOT-Contact-Single: Improving Single-Sequence-Based Prediction of Protein Contact Map using a Transformer Language Model, Large Training Set and Ensembled Deep Learning
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DDIG: Detecting DIsease-causing Genetic variations
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SPOT-Disorder-Single: Single Sequence Protein disorder prediction
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SPRINT-Gly: Predicting N- and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties
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SPIDER3: Capturing non-local interactions by long short term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers, and solvent accessibility
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SPOT-1D-LM:Reaching Alignment-profile-based Accuracy in Predicting Protein Secondary and Tertiary Structural Properties without Alignment
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SPOT-1D-Single: Improving the Single-Sequence-Based Prediction of Protein Secondary Structure, Backbone Angles, Solvent Accessibility and Half-Sphere Exposures using a Large Training Set and Ensembled Deep Learning
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SPOT-1D: Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks
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SPOT-Contact: Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks
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EASE-MM: Prediction of mutation-induced stability changes
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SPOT-Disorder: Protein disorder prediction v1.0
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SPOT-CBP: Template-based identification of carbohydrate-binding proteins
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SPOT-Disorder2: Protein disorder prediction
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SPOT-MoRF: Molecular recognition Features in Intrinsically Disordered Regions by Transfer Learning
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SPOT-Ligand2: Small molecule virtual screening by binding homology on expanded template library
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SPOT-Ligand: Small molecule virtual screening by binding homology search
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SPARKS-X: Protein fold recognition
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SPOT-peptide: Template-based prediction of peptide binding proteins and peptide binding sites
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SPOT-Contact: Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks