AIMC Topic: Amino Acid Sequence

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A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence.

ACS nano Jun 26, 2019
We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The soni...
Protein Conformation Protein Folding Artificial Intelligence Humans Proteins Mutation Models, Molecular Amino Acid Sequence Sound
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Analysis and prediction of human acetylation using a cascade classifier based on support vector machine.

BMC bioinformatics Jun 17, 2019
BACKGROUND: Acetylation on lysine is a widespread post-translational modification which is reversible and plays a crucial role in some biological activities. To better understand the mechanism, it is necessary to identify acetylation sites in protein...
Protein Processing, Post-Translational Proteins Databases, Protein Computational Biology Rats Support Vector Machine Molecular Sequence Annotation Gene Ontology Protein Structure, Secondary Amino Acid Sequence Acetylation Lysine Humans Animals Mice Position-Specific Scoring Matrices
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DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences.

PLoS computational biology Jun 14, 2019
Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature of in vitro and in vivo experiments have highlighted the importance of in silico-based DTI prediction approaches. In severa...
Models, Molecular Amino Acid Sequence Deep Learning Ligands Binding Sites Computer Simulation Computational Biology Sequence Analysis, Protein Drug Discovery Proteins
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Prediction of Enzyme Function Based on Three Parallel Deep CNN and Amino Acid Mutation.

International journal of molecular sciences Jun 11, 2019
During the past decade, due to the number of proteins in PDB database being increased gradually, traditional methods cannot better understand the function of newly discovered enzymes in chemical reactions. Computational models and protein feature rep...
Mutation Amino Acid Sequence Enzymes Neural Networks, Computer Animals Databases, Protein Humans
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ProteinNet: a standardized data set for machine learning of protein structure.

BMC bioinformatics Jun 11, 2019
BACKGROUND: Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like computer vision, progress has been driven by standardized ...
Reference Standards Sequence Alignment Proteins Databases, Protein Amino Acid Sequence Machine Learning
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An advanced approach to identify antimicrobial peptides and their function types for penaeus through machine learning strategies.

BMC bioinformatics Jun 10, 2019
BACKGROUND: Antimicrobial peptides (AMPs) are essential components of the innate immune system and can protect the host from various pathogenic bacteria. The marine environment is known to be one of the richest sources for AMPs. Effective usage of AM...
Machine Learning Antimicrobial Cationic Peptides Amino Acid Sequence Penaeidae Reproducibility of Results Animals Databases, Protein
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Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning.

BMC bioinformatics May 28, 2019
BACKGROUND: The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequencing technology enabled the...
Complementarity Determining Regions ROC Curve Receptors, Antigen, B-Cell Immunity, Humoral Immunoglobulins Humans Area Under Curve Databases, Genetic High-Throughput Nucleotide Sequencing Algorithms Supervised Machine Learning Amino Acid Motifs Tumor Microenvironment Amino Acid Sequence
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THPep: A machine learning-based approach for predicting tumor homing peptides.

Computational biology and chemistry May 24, 2019
In the present era, a major drawback of current anti-cancer drugs is the lack of satisfactory specificity towards tumor cells. Despite the presence of several therapies against cancer, tumor homing peptides are gaining importance as therapeutic agent...
ROC Curve Drug Delivery Systems Internet Neural Networks, Computer Neoplasms Decision Trees Amino Acid Sequence Machine Learning Peptides Databases, Protein Quantitative Structure-Activity Relationship
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Discrimination power of knowledge-based potential dictated by the dominant energies in native protein structures.

Amino acids May 16, 2019
Extracting a well-designed energy function is important for protein structure evaluation. Knowledge-based potential functions are one type of the energy functions which can be obtained from known protein structures. The pairwise potential between ato...
Amino Acid Sequence Knowledge Bases Hydrophobic and Hydrophilic Interactions Models, Molecular Proteins Protein Conformation Molecular Structure Entropy Amino Acids
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PiPred - a deep-learning method for prediction of π-helices in protein sequences.

Scientific reports May 3, 2019
Canonical π-helices are short, relatively unstable secondary structure elements found in proteins. They comprise seven or more residues and are present in 15% of all known protein structures, often in functionally important regions such as ligand- an...
Deep Learning Amino Acid Sequence Protein Conformation, alpha-Helical Computational Biology Proteins Models, Molecular
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