资 源 简 介
The proteomics comes into the high precision age. It is far from enough to simply improve the hardware performance of MS for acquiring high quality data. Re-calibration were verified to be an important way to improve the data accuracy significantly. By in-depth investigating the recalibration problem of MS data from high-thoughput experiments, FTDR was developed as a new framework to re-calibrate the mass to charge ratio (m/z) error of most observed parent ions to part per billion (ppb) level. FTDR 2.0 incorporated several efforts to share the ppb level accuracy in common experiments. Firstly, many new parameters were introduced and selected as features automatically to reduce the system error as much as possible and to adapt to various datasets. Secondly, a support vector regression (SVR) model was trained to character the complex non-linear maps from features to the m/z measurement errors. Thirdly, a specific m/z error tolerance (MET) for each parent ion was estimated by taking in
