Research On Algorithm For Mass Specerometry Based Proteomics

The aim of proteomics is to fully characterize proteins expressed in cell or tissue.Mass spectrometry is the key platform in proteomics for its sensitivity and accuracy.Data independent acquisition mode is a new mass spectrometry method developed to overcome disadvantage of data dependent acquisition mode.Since DIA mode select precursor ions unbiasedly,it's good for downstream quantification.But for its unbiased selection mode,raw data from DIA mode lacks relationship between precursor ion and product ion,which made it incompatible to available data analysis workflow.This paper divided into four sections : first,parameters of tuning and acquisition are optimized based on the instrument used in experiments and then modify a data acquisition mode which combine DIA and DDA mode;secondly,by means of molecular feature extraction,the molecular feature of DIA data were extracted,then local maximum algorithm were implemented to find elution profile of ions.The elution profile was then to be compared to reconstruct mass spectra containing relationship of precursor and product ions.Meanwhile,the usage of Kruskal algorithm helped to cluster mass spectra,which can reduce redundancy of data and decease time spend on database searching.Besides,to increase protein identified number and sequence coverage,a method based on complementary theory was tried,which can increase protein identified number and sequence coverage.Finally,to meet the needs of data analysis in big data time,a platform was established to integrate different result derived from varied algorithms and workflows to deeper analysis proteomics data.