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A better scoring model for de novo peptide sequencing: the symmetric difference between explained and measured masses

机译:从头测序的更好评分模型:解释质量与测量质量之间的对称差异

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摘要

BackgroundGiven a peptide as a string of amino acids, the masses of all its prefixes and suffixes can be found by a trivial linear scan through the amino acid masses. The inverse problem is the ideal de novo peptide sequencing problem: Given all prefix and suffix masses, determine the string of amino acids. In biological reality, the given masses are measured in a lab experiment, and measurements by necessity are noisy. The (real, noisy) de novo peptide sequencing problem therefore has a noisy input: a few of the prefix and suffix masses of the peptide are missing and a few other masses are given in addition. For this setting, we ask for an amino acid string that explains the given masses as accurately as possible.
机译:背景技术鉴于肽是一串氨基酸,可以通过对氨基酸质量进行简单的线性扫描来找到其所有前缀和后缀的质量。反问题是理想的从头肽测序问题:给定所有前缀和后缀质量,确定氨基酸串。在生物现实中,给定的质量是在实验室实验中测量的,而根据需要进行的测量是嘈杂的。因此,(真实的,嘈杂的)从头开始的肽测序问题有一个嘈杂的输入:缺少该肽的一些前缀和后缀质量,此外还给出了其他一些质量。对于此设置,我们要求提供一个氨基酸串,以尽可能准确地解释给定的质量。

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