通过双重质谱测量对的de-novo测序的算法:一篇综述
Cheuk Chi A Ng1, Yin Zhou1, Zhong-Ping Yao1
1State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China.
新的序测序使用质谱测量来确定未知的氨基酸序列. 先进的算法,包括机器学习,提高了生物和制药研究的准确性和速度.
科学领域:
- 化学和生物科学 化学和生物科学
- 医学和制药科学 医学和制药科学
背景情况:
- 序列测序对于化学,生物,药物和制药研究至关重要.
- 通过双重质谱法 (MS/MS) 的新序列测定是新鉴定的主要方法.
研究的目的:
- 审查和比较新的序算法.
- 突出数据集对算法性能的影响.
- 讨论当前的局限性和该领域的未来方向.
主要方法:
- 对算法的审查,从详尽的搜索到机器学习和神经网络.
- 分析MS/MS光谱以进行新的序测序.
- 基于各种数据集的算法性能比较.
主要成果:
- 先进的算法使准确和快速的新序列测序成为可能.
- 机器学习和神经网络方法代表了最先进的技术.
- 数据集的特征显著影响算法结果.
结论:
- De novo序测序是一个快速发展的领域,具有重大影响.
- 需要进一步开发以解决当前的局限性并增强高通量能力.
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