Investigation and Review of Efficient Method for Multiple Protein Network’s Pairwise Alignment
Smita Upendra Gumaste1, Jyoti Rao2

1Smita Upendra Gumaste, BE, Department of Computer Science and Engineering, India.
2Jyoti Rao, Assistant Professor, Department of Computer Engineering, DY Patil Institute of Engineering and Technology Pimpri Pune (Maharashtra), India.
Manuscript received on 12 March 2013 | Revised Manuscript received on 21 March 2013 | Manuscript Published on 30 March 2013 | PP: 150-154 | Volume-2 Issue-4, March 2013 | Retrieval Number: D0564032413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Since from last decade, there is rapid growth in the availability of data over the protein-protein interaction (PPI) networks considering the various species like human, fly, bacteria, yeast and worm. As we know that, one of the highly impacted approach for protein networks is that their comparative analysis which has already gain many researchers attention specially for the predicting the network structure, protein function as well as interaction. The major challenge for execution of this approach is to present robust algorithm for multiple network alignment. In this review paper, we are first presenting the literature review over the network alignment problems and querying problems. In the literature we are also discussing different PPI networks and their alignment problems. Further our main aim is to investigate the algorithm which is presented for efficient, fast with more accuracy pairwise alignment of multiple protein networks. Here we considering the proposed approach is work with novel representation of multiple protein networks those are having linear size. From the experiment and results observations, we found that this approach is more efficient and fast as compared to previous studies for multiple protein networks.
Keywords: Protein-Protein Interactions, Pairwise Alignment, Yeast Two-Hybrid, Data Representation, Search Methods.

Scope of the Article: Computer Network