Algorithms and software tools for analysis of mass spectrometry data

这项研究建议集中在生物信息学的一般领域，特别是基于蛋白质组学数据的质谱学计算分析。拟议的研究计划将重点放在肽、多糖和蛋白质的识别和质谱学分析的算法和软件工具上。长期目标是提供 生物和健康研究人员使用软件工具，利用质谱学对蛋白质进行表征。我们将开发新的算法，以帮助构建精度和质量更高的软件工具。在这项研究提案中，将追求四个短期目标： (1)提高抗体测序的准确性，验证抗体的完整质量：我们的研究将通过改进的二硫键连锁分析和重叠光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大规模验证问题。 (2)通过改进多光谱测序来提高多肽识别率：我们将开发新的算法来提高光谱相似性检测的效率。我们还将考虑从多个光谱中进行信息融合的新方法。 (3)提高复杂光谱的多肽识别率：对于涉及多个多肽的光谱，我们将扩展我们的二硫键连接分析工作，以包括两个二硫键，可能包含三个多肽。我们将为混合光谱测序设计新的技术。 (4)跟踪新的质谱学设备、新的实验方法和新的计算方法的发展。设计基于新技术的计算解决方案。 这项申请中的拟议研究将使有效的跨学科培训成为可能，将总部置于协作环境中。

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 provide biological 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.