Publication Type:

Conference Paper

Source:

Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore (2010)

ISBN:

9781450301947

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-78649407793&partnerID=40&md5=0e95fe569ba27ea606e12c6ef32ab325

Keywords:

chemical structure, Computational efficiency, Computing methods, Data sets, Drug discovery, Fast computation, Graph classification, graph kernel, Graph kernels, Kernel function, Sylvester equation, Time complexity, Two-dimensional graphical representation, virtual screening

Abstract:

We introduce a new kernel function called Fast computation of marginalized walk kernels for graph classification for the virtual screening in drug discovery. This kernel is an extension of marginalized graph kernels. In this paper we use two dimensional graphical representations of chemical structures. The similarity between molecules is measured by using kernel function. For reducing the time complexity of kernel computation we use fast computing methods like Sylvester equation. The efficiency is evaluated using MUTAG dataset. The results show that the new kernel function is more efficient than existing kernel. This gives the same accuracy with lesser time complexity. © 2010 ACM.

Notes:

cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@576040c5 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@703c7253 Through org.apache.xalan.xsltc.dom.DOMAdapter@1075e0b6; Conference Code:82507

Cite this Research Publication

M. P. Preeja and Soman, K. P., “Fast computation of marginalized walk kernel for virtual screening in drug discovery”, in Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore, 2010.