AIMC Topic: Amino Acid Sequence

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BepFAMN: A Method for Linear B-Cell Epitope Predictions Based on Fuzzy-ARTMAP Artificial Neural Network.

Sensors (Basel, Switzerland) May 26, 2022
The public health system is extremely dependent on the use of vaccines to immunize the population from a series of infectious and dangerous diseases, preventing the system from collapsing and millions of people dying every year. However, to develop t...
Area Under Curve Amino Acid Sequence Neural Networks, Computer Epitopes, B-Lymphocyte Humans
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A Deep Learning Model for Accurate Diagnosis of Infection Using Antibody Repertoires.

Journal of immunology (Baltimore, Md. : 1950) May 23, 2022
The adaptive immune receptor repertoire consists of the entire set of an individual's BCRs and TCRs and is believed to contain a record of prior immune responses and the potential for future immunity. Analyses of TCR repertoires via deep learning (DL...
COVID-19 Deep Learning Humans Amino Acid Sequence Receptors, Antigen, T-Cell
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Prediction of protein-protein interaction using graph neural networks.

Scientific reports May 19, 2022
Proteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein-protein interactio...
Saccharomyces cerevisiae Amino Acid Sequence Neural Networks, Computer Amino Acids Proteins Humans
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DLSSAffinity: protein-ligand binding affinity prediction a deep learning model.

Physical chemistry chemical physics : PCCP May 4, 2022
Evaluating the protein-ligand binding affinity is a substantial part of the computer-aided drug discovery process. Most of the proposed computational methods predict protein-ligand binding affinity using either limited full-length protein 3D structur...
Deep Learning Amino Acid Sequence Proteins Ligands Protein Binding
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LM-GVP: an extensible sequence and structure informed deep learning framework for protein property prediction.

Scientific reports Apr 27, 2022
Proteins perform many essential functions in biological systems and can be successfully developed as bio-therapeutics. It is invaluable to be able to predict their properties based on a proposed sequence and structure. In this study, we developed a n...
Deep Learning Proteins Language Amino Acid Sequence Neural Networks, Computer
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Performing protein fold recognition by exploiting a stack convolutional neural network with the attention mechanism.

Analytical biochemistry Apr 26, 2022
Protein fold recognition is a critical step in protein structure and function prediction, and aims to ascertain the most likely fold type of the query protein. As a typical pattern recognition problem, designing a powerful feature extractor and metri...
Proteins Amino Acid Sequence Algorithms Computational Biology Neural Networks, Computer
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Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics.

Journal of molecular biology Apr 22, 2022
The role of intrinsically disordered protein regions (IDRs) in cellular processes has become increasingly evident over the last years. These IDRs continue to challenge structural biology experiments because they lack a well-defined conformation, and ...
Sequence Analysis, Protein Intrinsically Disordered Proteins Protein Structure, Secondary Amino Acid Sequence Software Computational Biology Neural Networks, Computer
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DISTEMA: distance map-based estimation of single protein model accuracy with attentive 2D convolutional neural network.

BMC bioinformatics Apr 19, 2022
BACKGROUND: Estimation of the accuracy (quality) of protein structural models is important for both prediction and use of protein structural models. Deep learning methods have been used to integrate protein structure features to predict the quality o...
Deep Learning Neural Networks, Computer Amino Acid Sequence Proteins
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Prosit Transformer: A transformer for Prediction of MS2 Spectrum Intensities.

Journal of proteome research Apr 12, 2022
Machine learning has been an integral part of interpreting data from mass spectrometry (MS)-based proteomics for a long time. Relatively recently, a machine-learning structure appeared successful in other areas of bioinformatics, Transformers. Furthe...
Machine Learning Mass Spectrometry Proteomics Neural Networks, Computer Amino Acid Sequence
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Machine learning to navigate fitness landscapes for protein engineering.

Current opinion in biotechnology Apr 9, 2022
Machine learning (ML) is revolutionizing our ability to understand and predict the complex relationships between protein sequence, structure, and function. Predictive sequence-function models are enabling protein engineers to efficiently search the s...
Amino Acid Sequence Proteins Protein Engineering Biotechnology Machine Learning
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