Authors: Manish Kumar, Ruchi Verma & Gajendra Raghava
Prediction of mitochondrial proteins is one of the major challenge in the filed bioinformatics due to their importance living organism. Mitochondrial proteins are associated with diseases like Alzheimer, Perkinson and Type II diabetes. Thus it is important to develop method for predicting mitochondrial proteins. The existing subcellular localization methods predict most of the location with high accuracy except mitochondrial protein. In order to improve accuracy of prediction of mitochndrial protein we developed a novel method Mitpred, based on presence of exclusive mitochondrial domains.
Important points:
- SVM models using split amino acid composition (25 N-terminal, 25 C-terminal, and remaining residues)