A New Sequential Forward Feature Selection (SFFS) Algorithm for Mining Best Topological and Biological Features to Predict Protein Complexes from Protein-Protein Interaction Networks (PPINs).

Protein-protein interaction plays an important role in the understanding of biological processes in the body. A network of dynamic protein complexes within a cell that regulates most biological processes is known as a protein-protein interaction network (PPIN). Complex prediction from PPINs is a challenging task.

Combining SVM and ECOC for Identification of Protein Complexes from Protein Protein Interaction Networks by Integrating Amino Acids' Physical Properties and Complex Topology.

Protein Complexes plays important role in key functional processes in cells by forming Protein Protein Interaction (PPI) networks. Conventionally, they were determined through experimental approaches. For the sake of saving time and cost reduction, many computational methods have been proposed.