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Combining Sequence Entropy and Subgraph Topology for Complex Prediction in Protein Protein Interaction (PPI) Network

Author(s):

Aisha Sikandar, Muhammad Waqas Anwar* and Misba Sikandar  

Abstract:


Complex prediction from interaction network of proteins has become a challenging task. Most of the computational approaches focus on topological structures of protein complexes and fewer of them considers important biological information contained within amino acid sequences. To capture the essence of information contained within protein sequences we have computed sequence entropy and length. Proteins interact with each other and form different sub graph topologies. We integrate biological features with sub graph topology and model complexes by using a Logistic Model Tree. The experimental results demonstrated that our method out performs other four state-of-art computational methods in terms of the number of detecting known protein complexes correctly.

Keywords:

Protein Protein Interaction Sequence Entropy; Sub Graph Topology

Affiliation:

Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus



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