AIMC Topic: Dimerization

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Inter-protein residue covariation information unravels physically interacting protein dimers.

BMC bioinformatics
BACKGROUND: Predicting physical interaction between proteins is one of the greatest challenges in computational biology. There are considerable various protein interactions and a huge number of protein sequences and synthetic peptides with unknown in...

The Classifying Autoencoder: Gaining Insight into Amyloid Assembly of Peptides and Proteins.

The journal of physical chemistry. B
Despite the importance of amyloid formation in disease pathology, the understanding of the primary structure?activity relationship for amyloid-forming peptides remains elusive. Here we use a new neural-network based method of analysis: the classifyin...

Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

BMC bioinformatics
BACKGROUND: Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been develo...

Predicting bacterial virulence factors - evaluation of machine learning and negative data strategies.

Briefings in bioinformatics
Bacterial proteins dubbed virulence factors (VFs) are a highly diverse group of sequences, whose only obvious commonality is the very property of being, more or less directly, involved in virulence. It is therefore tempting to speculate whether their...