Computation and Bioinformatics for Proteomics
This course will cover the governing principles of analyzing proteomics data, with a special emphasis on data derived from mass spectrometry (MS). Computational methods and tutorials will complement the theoretical material.
Prerequisites: Enrollment in CAMS-MS program.
Outcomes: At the end of this course students will be able to: 1) Describe key approaches for matching MS spectra to known proteins, as well as identifying and quantifying protein content in analyzes samples; 2) Describe methodologies and limitations thereof for labeling and quantifying proteins of interest; 3) Perform routine computational analyses of MS data using python; and 4) Describe best-practices for objective data analysis and reproducibility.
Prerequisites: Enrollment in CAMS-MS program.
Outcomes: At the end of this course students will be able to: 1) Describe key approaches for matching MS spectra to known proteins, as well as identifying and quantifying protein content in analyzes samples; 2) Describe methodologies and limitations thereof for labeling and quantifying proteins of interest; 3) Perform routine computational analyses of MS data using python; and 4) Describe best-practices for objective data analysis and reproducibility.