A least square method based model for identifying protein complexes in protein-protein interaction network

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes.

Heart failure: advanced development in genetics and epigenetics

Heart failure (HF) is a complex pathophysiological syndrome that arises from a primary defect in the ability of the heart to take in and/or eject sufficient blood. Genetic mutations associated with familial dilated cardiomyopathy, hypertrophic cardiomyopathy, and arrhythmogenic right ventricular cardiomyopathy can contribute to the various pathologies of HF. Therefore, genetic screening could be an approach for guiding individualized therapies and surveillance. In addition, epigenetic regulation occurs via key mechanisms, including ATP-dependent chromatin remodeling, DNA methylation, histone modification, and RNA-based mechanisms. MicroRNA is also a hot spot in HF research. This review gives an overview of genetic mutations associated with cardiomyopathy and the roles of some epigenetic mechanisms in HF.