Algorithms and software tools for mass spectrometry data analysis and RNA structure analysis

拟议的研究计划将侧重于算法的开发和软件工具的构建，用于肽、聚糖和蛋白质的鉴定和质谱分析和RNA结构分析。拟议研究的长期目标是为生物和健康研究人员提供用质谱法表征蛋白质和分析RNA结构的软件工具。我们将开发新的算法来帮助构建具有更高准确性和质量的软件工具。在本研究计划中，将追求四个短期目标：(1)提高de novo测序肽鉴定率：de novo测序可以鉴定出任何数据库中不存在的新肽。我们的研究将解决与“混合”光谱相关的低识别率问题，其中两个或多个具有相似质量和保留时间的前体离子被MS/MS共洗脱。(2)提高从头开始的聚糖测序的准确性：我们将开发新的算法来解决当前测定聚糖结构方法准确性不足的问题。(3)利用MS/MS自动化全蛋白测序：我们将开发新的无模板蛋白全蛋白测序算法。(4)分析RNA-RNA相互作用结构：比较与推理：我们将研究RNA-RNA联合结构比较与推理问题的复杂性和设计算法。本申请中提出的研究将实现有效的跨学科培训，将HQP置于协作环境中。

The proposed research program will focus on the development of algorithms and the construction of software tools for peptide, glycan, and protein identification and analysis with mass spectrometry and RNA structure analysis. The long-term objective of the proposed research is to provide biological and health researchers with software tools for characterizing proteins with mass spectrometry and analyzing RNA structures. We will develop novel algorithms to help constructing software tools with improved accuracy and quality. Within this research proposal four short-term goals will be pursued: (1) Increase de novo sequencing peptide identification rate: De novo sequencing can identify novel peptides that do not exist in any database. Our research will address the low identification rate problem associated with the ''mixture'' spectra, where two or more precursor ions with similar mass and retention time are co-eluted by MS/MS. (2) Improve accuracy for de novo glycan sequencing: We will develop new algorithms to address the inadequate accuracy in current methods for the determination of glycan structure.(3) Automate complete protein sequencing with MS/MS: We will develop new algorithms for complete protein sequencing without template proteins.(4) Analyze RNA-RNA interaction structure: comparison and inference: We will study the complexity and design algorithms for RNA-RNA joint structure comparison and inference problems.The proposed research in this application will enable effective cross-disciplinary training, placing HQP in a collaborative environment.