alexa Abstract | Graph kernels and applications in protein classification

Journal of Chemical and Pharmaceutical Research
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Original Articles Open Access


Protein classification is a well established research field concerned with the discovery of molecule’s properties through informational techniques. Graph-based kernels provide a nice framework combining machine learning techniques with graph theory. In this paper we introduce a novel graph kernel method for annotating functional residues in protein structures. A structure¬ is first modeled as a protein contact graph, where nodes correspond to residues and edges connect spatially neighboring residues. In experiments on classification of graph models of proteins, the method based on Weisfeiler Lehman shortest path kernel with complement graphs outperformed other state-of-art methods.

To read the full article Peer-reviewed Article PDF image

Author(s): Jiang Qiangrong Xiong Zhikang and Zhai Can


Protein classification, Machine learning, Graph kernels, Shortest path, Weisfeiler-Lehman, protein

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version