Algorithms and software tools for analysis of mass spectrometry data

本研究计划侧重于生物信息学的一般领域，特别是基于质谱的蛋白质组学数据的计算分析。拟议的研究计划将集中在多肽、聚糖和蛋白质鉴定和质谱分析的算法和软件工具上。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，将实现四个短期目标：(1)提高抗体测序的准确性并验证抗体完整质量：我们的研究将通过改进二硫键连锁分析和重叠谱信息分析来提高抗体测序的质量。我们还将开发新的方法来解决抗体完整的质量验证。(2)通过改进多光谱测序提高多肽的识别率：我们将开发新的算法来提高光谱相似度检测的效率。我们还将考虑多光谱信息合并的新方法。(3)提高复杂光谱中肽的识别率：对于涉及多个肽的光谱，我们将扩展我们在二硫键连锁分析方面的工作，以包括可能包含三个肽的两个二硫键。我们将设计新的混合光谱测序技术。(4)跟踪新的质谱设备、新的实验方法和新的计算方法的发展。基于新技术设计计算解决方案。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。

This research proposal focuses on the general area of Bioinformatics, and in particular, on the computational analysis of mass spectrometry based proteomics data. The proposed research program will focus on algorithms and software tools for peptide, glycan, and protein identification and analysis with mass spectrometry. The long-term goal is to providebiological and health researchers with software tools for characterizing proteins with mass spectrometry. We will develop novel algorithms to help constructing software tools with improved accuracy and quality. Within this research proposal four short-term objectives will be pursued: (1) Increase the accuracy of antibody sequencing and validate antibody intact mass: Our research will improve the quality of antibody sequencing by improved disulfide bond linkage analysis and overlapping spectra information analysis. We will also develop new method to address antibody intact mass validation.(2) Increase peptide identification rate by improving multiple spectra sequencing: We will develop new algorithms to increase the efficiency of spectra similarity detection. We will also consider new methods for the information merge from multiple spectra.(3) Improve peptide identification rate for complex spectra: With spectra involving more than one peptides, we will extend our work on disulfide bond linkage analysis to include two disulfide bonds with possibly three peptides. We will design new techniques for the mixture spectra sequencing.(4) Follow the development of new mass spectrometry equipment, new experimental methods, and new computational approaches. Design computational solutions based on new technology.The proposed research in this application will enable effective cross-disciplinary training, placing HQP in a collaborative environment.