Hirakawa H, Kuhara S
Genome Inform Ser Workshop Genome Inform. 1997;8:61-70.
Information concerning the secondary structures, flexibility, epitope and hydrophobic regions of amino acid sequences can be extracted by assigning physicochemical indices to each amino acid residue, and information on structure can be derived using the sliding window averaging technique, which is in wide use for smoothing out raw functions. Wavelet analysis has shown great potential and applicability in many fields, such as astronomy, radar, earthquake prediction, and signal or image processing. This approach is efficient for removing noise from various functions. Here we employed wavelet analysis to smooth out a plot assigned to a hydrophobicity index for amino acid sequences. We then used the resulting function to predict hydrophobic cores in globular proteins. We calculated the prediction accuracy for the hydrophobic cores of 88 representative set of proteins. Use of wavelet analysis made feasible the prediction of hydrophobic cores at 6.13% greater accuracy than the sliding window averaging technique.
通过为每个氨基酸残基赋予物理化学指标，可以提取有关氨基酸序列二级结构、柔韧性、表位和疏水区域的信息，并且可以使用滑动窗口平均技术得出结构信息，该技术广泛用于平滑原始函数。小波分析在许多领域，如天文学、雷达、地震预测以及信号或图像处理中，已显示出巨大的潜力和适用性。这种方法对于从各种函数中去除噪声非常有效。在这里，我们采用小波分析来平滑分配给氨基酸序列疏水指数的图表。然后，我们使用所得函数预测球状蛋白质中的疏水核心。我们计算了88个代表性蛋白质组疏水核心的预测准确性。使用小波分析使得预测疏水核心的准确性比滑动窗口平均技术提高了6.13%，这成为可能。
