AIMC Topic: Amino Acid Sequence

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Learning meaningful representations of protein sequences.

Nature communications Apr 8, 2022
How we choose to represent our data has a fundamental impact on our ability to subsequently extract information from them. Machine learning promises to automatically determine efficient representations from large unstructured datasets, such as those ...
Machine Learning Amino Acid Sequence
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XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set.

Scientific reports Apr 1, 2022
Accurate identification of drug-targets in human body has great significance for designing novel drugs. Compared with traditional experimental methods, prediction of drug-targets via machine learning algorithms has enhanced the attention of many rese...
Humans Machine Learning Amino Acids Amino Acid Sequence Algorithms Proteins
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GEFA: Early Fusion Approach in Drug-Target Affinity Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Apr 1, 2022
Predicting the interaction between a compound and a target is crucial for rapid drug repurposing. Deep learning has been successfully applied in drug-target affinity (DTA)problem. However, previous deep learning-based methods ignore modeling the dire...
Drug Development Neural Networks, Computer Drug Repositioning Proteins Amino Acid Sequence
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PhosVarDeep: deep-learning based prediction of phospho-variants using sequence information.

PeerJ Mar 14, 2022
Human DNA sequencing has revealed numerous single nucleotide variants associated with complex diseases. Researchers have shown that these variants have potential effects on protein function, one of which is to disrupt protein phosphorylation. Based o...
Deep Learning Amino Acid Sequence Machine Learning Proteins Humans Algorithms
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Large-scale design and refinement of stable proteins using sequence-only models.

PloS one Mar 14, 2022
Engineered proteins generally must possess a stable structure in order to achieve their designed function. Stable designs, however, are astronomically rare within the space of all possible amino acid sequences. As a consequence, many designs must be ...
Amino Acid Sequence Protein Stability Proteins Neural Networks, Computer Amino Acids
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iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Immunogenetics Mar 5, 2022
Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a promising role in cancer treatment. Since experimental methods are still expensive and time-consuming, it is highly desirable to develop automatic com...
Algorithms T-Lymphocytes Humans Membrane Proteins Support Vector Machine Neoplasms Computational Biology Mitochondrial Proteins Amino Acids Amino Acid Sequence
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Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction.

Journal of chemical information and modeling Feb 24, 2022
Identifying drug-protein interactions (DPIs) is crucial in drug discovery, and a number of machine learning methods have been developed to predict DPIs. Existing methods usually use unrealistic data sets with hidden bias, which will limit the accurac...
Amino Acid Sequence Neural Networks, Computer Machine Learning Deep Learning Proteins
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ACPNet: A Deep Learning Network to Identify Anticancer Peptides by Hybrid Sequence Information.

Molecules (Basel, Switzerland) Feb 24, 2022
Cancer is one of the most dangerous threats to human health. One of the issues is drug resistance action, which leads to side effects after drug treatment. Numerous therapies have endeavored to relieve the drug resistance action. Recently, anticancer...
Deep Learning Amino Acid Sequence Peptides Antineoplastic Agents Humans Neoplasms
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Using deep learning to annotate the protein universe.

Nature biotechnology Feb 21, 2022
Understanding the relationship between amino acid sequence and protein function is a long-standing challenge with far-reaching scientific and translational implications. State-of-the-art alignment-based techniques cannot predict function for one-thir...
Molecular Sequence Annotation Proteomics Proteome Databases, Protein Amino Acid Sequence Humans Deep Learning
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Machine Learning Approaches for Metalloproteins.

Molecules (Basel, Switzerland) Feb 14, 2022
Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts...
Protein Binding Structure-Activity Relationship Models, Molecular Amino Acid Sequence Binding Sites Protein Stability Metalloproteins Proteolysis Machine Learning Drug Design
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