AIMC Topic: Proteins

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BioKA: a curated and integrated biomarker knowledgebase for animals.

Nucleic acids research
Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap i...

Simulations of Sequence Evolution: How (Un)realistic They Are and Why.

Molecular biology and evolution
MOTIVATION: Simulating multiple sequence alignments (MSAs) using probabilistic models of sequence evolution plays an important role in the evaluation of phylogenetic inference tools and is crucial to the development of novel learning-based approaches...

Estimating protein-ligand interactions with geometric deep learning and mixture density models.

Journal of biosciences
Understanding the interactions between a ligand and its molecular target is crucial in guiding the optimization of molecules for any drug design workflow. Multiple experimental and computational methods have been developed to better understand these...

Advances in Protein-Ligand Binding Affinity Prediction via Deep Learning: A Comprehensive Study of Datasets, Data Preprocessing Techniques, and Model Architectures.

Current drug targets
BACKGROUND: Drug discovery is a complex and expensive procedure involving several timely and costly phases through which new potential pharmaceutical compounds must pass to get approved. One of these critical steps is the identification and optimizat...

AI-Assisted Processing Pipeline to Boost Protein Isoform Detection.

Methods in molecular biology (Clifton, N.J.)
Proteomics, the study of proteins within biological systems, has seen remarkable advancements in recent years, with protein isoform detection emerging as one of the next major frontiers. One of the primary challenges is achieving the necessary peptid...

Assessment of Protein-Protein Docking Models Using Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions are involved in almost all processes in a living cell and determine the biological functions of proteins. To obtain mechanistic understandings of protein-protein interactions, the tertiary structures of protein complexes ...

Machine Learning Methods in Protein-Protein Docking.

Methods in molecular biology (Clifton, N.J.)
An exponential increase in the number of publications that address artificial intelligence (AI) usage in life sciences has been noticed in recent years, while new modeling techniques are constantly being reported. The potential of these methods is va...

LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.

Current pharmaceutical design
INTRODUCTION: Drug development is a challenging and costly process, yet it plays a crucial role in improving healthcare outcomes. Drug development requires extensive research and testing to meet the demands for economic efficiency, cures, and pain re...

Recent Advances in Protein Folding Pathway Prediction through Computational Methods.

Current medicinal chemistry
The protein folding mechanisms are crucial to understanding the fundamental processes of life and solving many biological and medical problems. By studying the folding process, we can reveal how proteins achieve their biological functions through spe...

Comprehensive Review on Drug-target Interaction Prediction - Latest Developments and Overview.

Current drug discovery technologies
Drug-target interactions (DTIs) are an important part of the drug development process. When the drug (a chemical molecule) binds to a target (proteins or nucleic acids), it modulates the biological behavior/function of the target, returning it to its...