• The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches.

    程序会把核苷酸或者蛋白质的序列与序列数据库相比较,并计算符合的统计学意义。

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  • In one demonstration they undertook a project for Seattle Children's Hospital to examine the interrelationships of known protein sequences.

    在一个演示中,它们采用了西雅图儿童医院的一个项目来检验已知蛋白质序列的相互关系。

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  • Nucleotide and protein sequences are the foundation for all bioinformatics tools and resources.

    核酸和蛋白质序列是所有生物信息学工具和资源的基础。

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  • Phylogenetic analysis has been used to study the evolutionary relationship among DNA and protein sequences of various organisms extensively.

    系统发生分析被广泛应用于研究不同生物DNA、蛋白质序列的进化关系。

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  • With the success of human genome project, a widening gap appears between rapidly increasing known protein sequences and slow accumulation of known protein structures.

    随着人类基因组计划的顺利实施,蛋白质序列信息的积累速度远快于蛋白质结构数量的增长速度。

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  • This database contains all publicly available nucleotide and derived protein sequences.

    这个数据库包含所有公开可用的核酸和衍生的蛋白质序列。

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  • The notion of measure representation of complete genomes and protein sequences is introduced.

    介绍了关于完全基因组及蛋白质序列的测度表示。

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  • The comparability of the protein sequences of CRHR1 and CRHR2 of pig with other mammals are more than 97% and 88% respectively.

    猪CRHR1和CRHR2氨基酸序列与其它哺乳动物同源的氨基酸序列比较,相似性分别达97%和88%以上。

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  • Increasing protein sequences from the genome project require theoretical methods to predict transmembrane helical segments (TMHs).

    基因组计划所产生的大量蛋白质序列迫切需要从理论上预测跨膜螺旋区段。

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  • The IFS model and recurrent IFS (RIFS) model are proposed to simulate the measure representation of complete genomes and protein sequences.

    在此我们提出用IFS模型及递归的IFS (RIFS)模型来拟合完全基因组与蛋白质序列的测度表示。

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  • Three clones of LW20, LW22 and LW24 had unmatched protein sequences in database, they might be representative of one part of a unknown gene.

    在数据库中,均未发现与LW20、LW22和LW24三个克隆相匹配的蛋白质序列,推测可能为新基因的一部分。

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  • FDOD describes protein primary sequences by their subsequence distributions, therefore, the information of protein sequences is sufficiently taken into account.

    该方法用蛋白质原始序列的子序列分布来描述氨基酸序列,从而充分考虑了蛋白质序列的信息。

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  • Amino acid numeric coding model is used to convert protein sequences into numeric sequences, and the protein Hasse matrix is constructed based on partial ordering.

    利用氨基酸数字编码模型,将蛋白质序列转换为数字序列,根据偏序理论构建蛋白质哈斯矩阵。

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  • The process is carried out computationally in a high throughput manner by mining the ever-expanding databases of protein sequences of all organisms, especially human.

    该方法通过挖掘不断膨胀的所有生物、特别是人类的蛋白质序列数据库,以高通量的方式在计算机上进行。

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  • We randomly concatenate the protein sequences with the same function one by one to get a long linked protein sequence. We call these linked protein sequences as linked functional protein sequences.

    我们将具有相同功能的蛋白质序列随机地连接成一条长的序列,这些连接而成的长的蛋白质序列被称为连接的功能蛋白序列。

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  • We randomly concatenate the protein sequences with the same function one by one to get a long linked protein sequence. We call these linked protein sequences as linked functional protein sequences.

    我们将具有相同功能的蛋白质序列随机地连接成一条长的序列,这些连接而成的长的蛋白质序列被称为连接的功能蛋白序列。

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