Visualization of protein structure relationships using constrained twin kernel embedding

Yi Guo, Jun-Bin Gao, Paul Kwan, Xinsheng Hou

School of Biological, Biomedical and Molecular Sciences University of New England.
School of Computer Science Charles Sturt University.
School of Science and Technology University of New England.

DOI: 10.4236/jbise.2008.12022                

Abstract

In this paper, a recently proposed dimensional-ity reduction method called Twin Kernel Em-bedding (TKE) [10] is applied in 2-dimensional visualization of protein structure relationships. By matching the similarity measures of the input and the embedding spaces expressed by their respective kernels, TKE ensures that both local and global proximity information are preserved simultaneously. Experiments conducted on a subset of the Structural Classification Of Pro-tein (SCOP) database confirmed the effective-ness of TKE in preserving the original relation-ships among protein structures in the lower di-mensional embedding according to their simi-larities. This result is expected to benefit sub-sequent analyses of protein structures and their functions.

Keywords

Visualization of protein structure, Constrained twin kernel embedding

Conflicts of Interest

The authors declare no conflicts of interest.

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