公开(公告)号：US07136759B2

公开(公告)日：2006-11-14

申请号：US10323387

申请日：2002-12-18

申请人： Lars J. Kangas ,  Kenneth J. Auberry ,  Gordon A. Anderson ,  Richard D. Smith

发明人： Lars J. Kangas ,  Kenneth J. Auberry ,  Gordon A. Anderson ,  Richard D. Smith

IPC分类号： G06F17/11 ,  G06F17/50 ,  G06F19/00

CPC分类号： G01N30/8693 ,  G01N33/6806 ,  G01N2030/8831 ,  G06F19/24

摘要： A method for predicting the elution time of a peptide in chromatographic and electrophoretic separations by first providing a data set of known elution times of known peptides, then creating a plurality of vectors, each vector having a plurality of dimensions, and each dimension representing the elution time of amino acids present in each of these known peptides from the data set. The elution time of any protein is then be predicted by first creating a vector by assigning dimensional values for the elution time of amino acids of at least one hypothetical peptide and then calculating a predicted elution time for the vector by performing a multivariate regression of the dimensional values of the hypothetical peptide using the dimensional values of the known peptides. Preferably, the multivariate regression is accomplished by the use of an artificial neural network and the elution times are first normalized using a transfer function.

摘要翻译： 一种通过首先提供已知肽的已知洗脱时间的数据集，然后产生多个载体，每个载体具有多个维度，并且每个维度代表洗脱的方法，用于预测肽在色谱和电泳分离中的洗脱时间的方法 来自数据集的这些已知肽各自存在的氨基酸的时间。 然后通过首先通过分配至少一个假想肽的氨基酸的洗脱时间的维度值来产生载体，然后通过执行尺寸的多元回归来计算载体的预测洗脱时间来预测任何蛋白质的洗脱时间 使用已知肽的尺寸值的假想肽的值。 优选地，通过使用人造神经网络实现多元回归，并且首先使用传递函数归一化洗脱次数。