AIMC Topic: Protein Interaction Mapping

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Improved in Silico Identification of Protein-Protein Interactions Using Deep Learning Approach.

IET systems biology
Protein-protein interactions (PPIs) perform significant functions in many biological activities likewise gene regulation, metabolic pathways and signal transduction. The deregulation of PPIs may cause deadly diseases, such as cancer, autoimmune, pern...

EuDockScore: Euclidean graph neural networks for scoring protein-protein interfaces.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interactions are essential for a variety of biological phenomena including mediating biochemical reactions, cell signaling, and the immune response. Proteins seek to form interfaces which reduce overall system energy. Alth...

New GO-based measures in multiple network alignment.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction (PPI) networks provide valuable insights into the function of biological systems. Aligning multiple PPI networks may expose relationships beyond those observable by pairwise comparisons. However, assessing the ...

Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network.

Briefings in bioinformatics
Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to en...

INTREPPPID-an orthologue-informed quintuplet network for cross-species prediction of protein-protein interaction.

Briefings in bioinformatics
An overwhelming majority of protein-protein interaction (PPI) studies are conducted in a select few model organisms largely due to constraints in time and cost of the associated 'wet lab' experiments. In silico PPI inference methods are ideal tools t...

DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.

Nucleic acids research
Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting t...

MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achi...

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...