This paper applies discrete wavelet transform (DWT) with various protein substitution models to find functional similarity of proteins with low identity. A new metric, 'S' function, based on the DWT is proposed to measure the pair-wise similarity. We also develop a segmentation technique, combined with DWT, to handle long protein sequences. The results are compared with those using the pair-wise alignment and PSI-BLAST.

The potential of support vector machines (SVMs) for the substructure elucidation of infrared spectra have been investigated. The trained SVMs can identify the 16 substructures with high accuracy.

In this paper, a new hybrid model of amino acid substitution is developed and compared with the others in previous works. The results show that the new hybrid model can characterize the protein sequences very well by calculating Fisher weights, which can denote how much the variants contribute to the classification.

Although the sequence information on G-protein coupled receptors (GPCRs) continues to grow, many GPCRs remain orphaned (i.e. ligand specificity unknown) or poorly characterized with little structural information available, so an automated and reliable method is badly needed to facilitate the identification of novel receptors. In this study, a method of fast Fourier transform-based support vector machine has been developed for predicting GPCR subfamilies according to protein's hydrophobicity. In classifying Class B, C, D and F subfamilies, the method achieved an overall Matthew's correlation coefficient and accuracy of 0.95 and 93.3%, respectively, when evaluated using the jackknife test. The method achieved an accuracy of 100% on the Class B independent dataset. The results show that this method can classify GPCR subfamilies as well as their functional classification with high accuracy. A web server implementing the prediction is available at http://chem.scu.edu.cn/blast/Pred-GPCR.

Simultaneous determination of tin, germanium and molybdenum in food samples has been established by flow injection-charge coupled detector (CCD) diode array detection spectrophotometry with partial least squares (PLS) algorithm. The methodwas based on the chromogenic reaction of metal ions and salicylflurone in the presence of cetyltrimethyl ammonium bromide. The overlapping spectra of these complexes are collected by CCD diode array detector and the multi-wavelength absorbance data are processed using partial least squares algorithm. The reaction conditions and analytical parameters of flow injection analysis have been investigated. The method was applied to directly determine Ge, Mo and Sn in several food samples after digestion with satisfactory results. The recoveries of spiked samples were 80.0-102.0% for tin, 86.3-92.0% for germanium and 83.2-95.2% for molybdenum, and the relative standard deviations for samples were 4.4-7.8%. Molybdenum in certified reference material of cattle liver was determined by the proposed method (n=8). The differential values between determined and guarantee values were within the given uncertain value ranges (t=1.687,P>0.05 for t-test). The samples of mung bean, kelp and pork liver were analyzed by the proposed method and inductively couple plasma-atomic emission spectroscopy (ICP-AES) method. The determination results of the two methods are in good agreement. The sampling rate is 30 samples h−1.