演講研討會公告
Prosit: Using deep learning to generate proteome-wide spectral libraries of (un)modified (non-)tryptic peptides
2019-09-10 11:00 ~ 2019-09-10 12:00
地點: 生化所209室
主講人: Dr. Mathias Wilhelm
主講人背景: 德國慕尼黑工業大學生物資訊組組長
主講人網站: https://proteomics.wzw.tum.de/index.php?id=48
演講主持人: 邱繼輝特聘研究員
演講摘要:
The fragmentation pattern and retention time of a peptide are (currently) two of the most important features for any mass spectrometry-based proteomics method. However, the generation of comprehensive proteome-wide spectral libraries is time consuming and arguable not possible. Because of this, spectral libraries generated from prior DDA experiments are an essential step before conducting DIA or PRM experiments. Here, we show how Prosit, our deep-learning framework for predicting fragment intensities and retention times of peptides, can be used to generate proteome-wide in-silico spectral libraries with near reference data quality for virtually any (un)modified (non-)tryptic peptide irrespective of its origin. Because Prosit was trained on systematically acquired data from the ProteomeTools project, it is able to predict spectra at any commonly used collision energy. This allows users to calibrate predictions to their mass spectrometer avoiding time-consuming re-training. We show that our predictions allow the confident identification of peptides when investigating excessively large search spaces by DDA, perform on par with custom spectral libraries when analyzing DIA data and can be used to speed up assay development using MRM or PRM acquisition schemes.-Dr. Mathias Wilhelm
洽詢人員: 劉小姐
洽詢電話: 02-27855696#2061
洽詢信箱: liukchun@gate.sinica.edu.tw