A new graph-based method for global alignment of protein–protein interaction networks

سال انتشار: 1392
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 651

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شناسه ملی سند علمی:

NBCI08_1060

تاریخ نمایه سازی: 29 شهریور 1394

چکیده مقاله:

Motivation: The interactions among proteins and the resulting net- works of such interactions have acentral role in cell biology. Aligning these networks gives us important information, such as con- served complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks; however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple align- ment of several large networks together.Results: We present a novel algorithm for the global alignment of protein–protein interaction networks. It uses a greedy method, based on the alignment scoring matrix, which is derived from both biological and topological information of input networks to find the best global network alignment. NETAL outperforms other global alignment methods in terms of several measurements, such as Edge Correctness, Largest Common Connected Subgraphs and the number of common Gene Ontology terms between aligned proteins. As the running time of NETAL is much less than other available methods, NETAL can be easily expanded to multiple alignment algorithm. Furthermore, NETAL overpowers all other existing algorithms in term of performance so that the short running time of NETAL allowed us to implement it as the first server for global alignment of protein–protein interaction networks. Availability: Binaries supported on linux are freely available for download at http://www.bioinf.cs.ipm.ir/software/netal.

نویسندگان

Behnam Neyshabur

۱Department of Computer Engineering, Sharif University of Technology

Ahmadreza Khadem

۱Department of Computer Engineering, Sharif University of Technology

Somaye Hashemifar

۲School of Computer Science, University of Tehran

Seyed Shahriar Arab

۳Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University ۴Bioinformatics Department, School of Computer Science, Institute for Research in Fundamental Science (IPM), Tehran, Iran