Visualization of Protein Structure Relationships Using Twin Kernel Embedding

Yi Guo, Junbin Gao, Paul Kwan, Kevin Hou

    Research output: Book chapter/Published conference paperConference paperpeer-review

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    In this paper, a recently proposed dimensionality reduction method called Twin Kernel Embedding (TKE) 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 Protein (SCOP) database confirmed the effectiveness of TKE in preserving the original relationships among protein structures in the lower dimensional embedding according to their similarities. This result is expected to benefit subsequent analyses of protein structures and their functions.
    Original languageEnglish
    Title of host publicationICBBE2007
    EditorsYuanhan Lei
    Place of PublicationWashington DC, USA
    Number of pages4
    ISBN (Electronic)1424411203
    Publication statusPublished - 2007
    EventInternational Conference on Bioinformatics and Biomedical Engineering (ICBBE) - Wuhan, China, China
    Duration: 06 Jul 200708 Jul 2007


    ConferenceInternational Conference on Bioinformatics and Biomedical Engineering (ICBBE)


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