Net2Align: An Algorithm For Pairwise Global Alignment of Biological Networks



Priyanka Narad*#a, Ankur Chaurasia #a, Gulshan Wadhwab and K. C. Upadhyayaa



aAmity Institute of Biotechnology, Amity University Uttar Pradesh, U.P., India; bJoint Director, Department of Biotechnology, CGO Complex, New Delhi, India;



Priyanka Narad - Email id:, Contact No. +91-9999302904; *Corresponding author # Both authors contributed equally


Article Type

Prediction Model



Received October 17, 2016; Accepted November 13, 2016; Published December 4, 2016



The amount of data on molecular interactions is growing at an enormous pace, whereas the progress of methods for analysing this data is still lacking behind. Particularly, in the area of comparative analysis of biological networks, where one wishes to explore the similarity between two biological networks, this holds a potential problem. In consideration that the functionality primarily runs at the network level, it advocates the need for robust comparison methods. In this paper, we describe Net2Align, an algorithm for pairwise global alignment that can perform node-to-node correspondences as well as edge-to-edge correspondences into consideration. The uniqueness of our algorithm is in the fact that it is also able to detect the type of interaction, which is essential in case of directed graphs. The existing algorithm is only able to identify the common nodes but not the common edges. Another striking feature of the algorithm is that it is able to remove duplicate entries in case of variable datasets being aligned. This is achieved through creation of a local database which helps exclude duplicate links. In a pervasive computational study on gene regulatory network, we establish that our algorithm surpasses its counterparts in its results. Net2Align has been implemented in Java 7 and the source code is available as supplementary files.



Algorithm, Pairwise Global Alignment, Biological Networks



Narad et al. Bioinformation 12(12): 408-411 (2016)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.