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Ding C.H., I. Dubchak. “Multi–class protein fold recognition using support vector machines and neural networks”. Bioinformatics 17,2001,pp. 349–358.

has been cited by the following article:

• TITLE: Hilbert Huang Transform for Predicting Proteins Subcellular Location

  AUTHORS: Feng SHI, Qiujian CHEN, Nana LI

  KEYWORDS: Hilbert Huang transform, support vector machine, subcellular location predict

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.1 No.1, June 6, 2008

  ABSTRACT: Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death, and their function is related to their types. The apoptosis proteins are categorized into the following four types: (1) Cytoplasmic protein; (2) Plasma membrane-bound protein; (3) Mitochondrial inner and outer proteins; (4) Other proteins. A novel method, the Hilbert-Huang transform, is applied for predicting the type of a given apoptosis protein with support vector machine. High success rates were obtained by the re-substitute test (98/98=100%), jackknife test (91/98 = 92.9%).