AIMC Topic: Amino Acid Sequence

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How Deep Learning Tools Can Help Protein Engineers Find Good Sequences.

The journal of physical chemistry. B Jun 9, 2021
The deep learning revolution introduced a new and efficacious way to address computational challenges in a wide range of fields, relying on large data sets and powerful computational resources. In protein engineering, we consider the challenge of com...
Proteins Amino Acid Sequence Protein Engineering Deep Learning
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Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.

International journal of molecular sciences Jun 2, 2021
The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins' 3D structural components is now heavily dependent on machine learning techniques tha...
Evolution, Molecular Databases, Protein Amino Acid Sequence Humans Software Neural Networks, Computer Deep Learning Protein Conformation Machine Learning Computational Biology Sequence Alignment
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Protein sequence design with deep generative models.

Current opinion in chemical biology May 26, 2021
Protein engineering seeks to identify protein sequences with optimized properties. When guided by machine learning, protein sequence generation methods can draw on prior knowledge and experimental efforts to improve this process. In this review, we h...
Amino Acid Sequence Protein Engineering Machine Learning
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Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides.

International journal of molecular sciences May 26, 2021
Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop ...
Sheep Hemolysis Amino Acid Sequence HeLa Cells Humans Neoplasms Machine Learning Peptides Databases, Protein Animals Antineoplastic Agents MCF-7 Cells A549 Cells
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Structure-based protein function prediction using graph convolutional networks.

Nature communications May 26, 2021
The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, we introduce DeepFRI, a Graph Convolutional Network for predicting pro...
Amino Acid Sequence Datasets as Topic Protein Structure, Tertiary Structure-Activity Relationship Models, Molecular Models, Biological Deep Learning Computational Biology Proteins Databases, Protein
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Improvement of Neoantigen Identification Through Convolution Neural Network.

Frontiers in immunology May 25, 2021
Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are lim...
Epitope Mapping Amino Acid Motifs Antigen Presentation Antigens, Neoplasm Algorithms HLA Antigens Alleles Biomarkers, Tumor Epitopes Amino Acid Sequence Computational Biology Conserved Sequence Humans Neural Networks, Computer
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Deep Learning-Based Advances in Protein Structure Prediction.

International journal of molecular sciences May 24, 2021
Obtaining an accurate description of protein structure is a fundamental step toward understanding the underpinning of biology. Although recent advances in experimental approaches have greatly enhanced our capabilities to experimentally determine prot...
Deep Learning Computational Biology Proteins Databases, Protein Models, Molecular Amino Acid Sequence Protein Conformation Neural Networks, Computer Cryoelectron Microscopy Software Sequence Analysis, Protein Algorithms
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Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins.

Journal of translational medicine May 24, 2021
BACKGROUND: Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the...
Phosphorylation Amino Acid Sequence Machine Learning Computational Biology Proteins
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Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides.

Scientific reports May 20, 2021
Cell-penetrating peptides have important therapeutic applications in drug delivery, but the variety of known cell-penetrating peptides is still limited. With a promise to accelerate peptide development, artificial intelligence (AI) techniques includi...
Humans HeLa Cells Cell Membrane Cell-Penetrating Peptides Cell Survival Artificial Intelligence Molecular Dynamics Simulation Reproducibility of Results Amino Acid Sequence
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Protein transfer learning improves identification of heat shock protein families.

PloS one May 18, 2021
Heat shock proteins (HSPs) play a pivotal role as molecular chaperones against unfavorable conditions. Although HSPs are of great importance, their computational identification remains a significant challenge. Previous studies have two major limitati...
Protein Transport Humans Neural Networks, Computer Molecular Chaperones Computational Biology Machine Learning Algorithms Amino Acid Sequence Deep Learning Heat-Shock Proteins
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