Protein Homology Detection Through Alignment of Markov Random Fields: Using MRFalign

This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications.

The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors.

MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction.

The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method.