AI Medical Compendium Topic:
Proteins

Clear Filters Showing 521 to 530 of 1866 articles

Protein-DNA Binding Residue Prediction via Bagging Strategy and Sequence-Based Cube-Format Feature.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-DNA interactions play an important role in diverse biological processes. Accurately identifying protein-DNA binding residues is a critical but challenging task for protein function annotations and drug design. Although wet-lab experimental me...

Accurate Prediction of Human Essential Proteins Using Ensemble Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Essential proteins are considered the foundation of life as they are indispensable for the survival of living organisms. Computational methods for essential protein discovery provide a fast way to identify essential proteins. But most of them heavily...

New Labeling Methods for Deep Learning Real-Valued Inter-Residue Distance Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
BACKGROUND: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction-a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorit...

TripletProt: Deep Representation Learning of Proteins Based On Siamese Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Pretrained representations have recently gained attention in various machine learning applications. Nonetheless, the high computational costs associated with training these models have motivated alternative approaches for representation learning. Her...

Multi-dimensional feature recognition model based on capsule network for ubiquitination site prediction.

PeerJ
Ubiquitination is an important post-translational modification of proteins that regulates many cellular activities. Traditional experimental methods for identification are costly and time-consuming, so many researchers have proposed computational met...

Convolutional ProteinUnetLM competitive with long short-term memory-based protein secondary structure predictors.

Proteins
The protein secondary structure (SS) prediction plays an important role in the characterization of general protein structure and function. In recent years, a new generation of algorithms for SS prediction based on embeddings from protein language mod...

Long-distance dependency combined multi-hop graph neural networks for protein-protein interactions prediction.

BMC bioinformatics
BACKGROUND: Protein-protein interactions are widespread in biological systems and play an important role in cell biology. Since traditional laboratory-based methods have some drawbacks, such as time-consuming, money-consuming, etc., a large number of...

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition.

International journal of molecular sciences
The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information i...

AlphaFill: enriching AlphaFold models with ligands and cofactors.

Nature methods
Artificial intelligence-based protein structure prediction approaches have had a transformative effect on biomolecular sciences. The predicted protein models in the AlphaFold protein structure database, however, all lack coordinates for small molecul...

End-to-End Protein Normal Mode Frequency Predictions Using Language and Graph Models and Application to Sonification.

ACS nano
The prediction of mechanical and dynamical properties of proteins is an important frontier, especially given the greater availability of proteins structures. Here we report a series of models that provide end-to-end predictions of nanodynamical prope...