AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Amino Acid Sequence

Showing 161 to 170 of 664 articles

Clear Filters

Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method.

Computers in biology and medicine
Drug targets must be identified and positioned correctly to research and manufacture new drugs. In this study, rather than using traditional methods for drug expansion, the drug target is determined using machine learning. Machine learning has genera...

Collectively encoding protein properties enriches protein language models.

BMC bioinformatics
Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such protein language mod...

DeepCPPred: A Deep Learning Framework for the Discrimination of Cell-Penetrating Peptides and Their Uptake Efficiencies.

IEEE/ACM transactions on computational biology and bioinformatics
Cell-penetrating peptides (CPPs) are special peptides capable of carrying a variety of bioactive molecules, such as genetic materials, short interfering RNAs and nanoparticles, into cells. Recently, research on CPP has gained substantial interest fro...

An interpretable deep learning model for classifying adaptor protein complexes from sequence information.

Methods (San Diego, Calif.)
Adaptor proteins (APs) are a family of proteins that aids in intracellular membrane trafficking, and their impairments or defects are closely related to various disorders. Traditional methods to identify and classify APs require time and complex tech...

Discovering design principles of collagen molecular stability using a genetic algorithm, deep learning, and experimental validation.

Proceedings of the National Academy of Sciences of the United States of America
Collagen is the most abundant structural protein in humans, providing crucial mechanical properties, including high strength and toughness, in tissues. Collagen-based biomaterials are, therefore, used for tissue repair and regeneration. Utilizing col...

Graph Neural Network for Protein-Protein Interaction Prediction: A Comparative Study.

Molecules (Basel, Switzerland)
Proteins are the fundamental biological macromolecules which underline practically all biological activities. Protein-protein interactions (PPIs), as they are known, are how proteins interact with other proteins in their environment to perform biolog...

Robust deep learning-based protein sequence design using ProteinMPNN.

Science (New York, N.Y.)
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based pro...

Protein secondary structure assignment using residual networks.

Journal of molecular modeling
Proteins are constructed from amino acid sequences. Their structural classifications include primary, secondary, tertiary, and quaternary, with tertiary and quaternary structures influencing protein function. Because a protein's structure is inextric...

A deep learning method for predicting molecular properties and compound-protein interactions.

Journal of molecular graphics & modelling
Predicting molecular properties and compound-protein interactions (CPIs) are two important areas of drug design and discovery. They are also an essential way to discover lead compounds in virtual screening. Recently, in silico methods based on deep l...

NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning.

Frontiers in immunology
Antibodies are a rapidly growing class of therapeutics. Recently, single domain camelid VHH antibodies, and their recognition nanobody domain (Nb) appeared as a cost-effective highly stable alternative to full-length antibodies. There is a growing ne...