One effective way of identifying posttranslational modification is to compare the empirically determined protein isoelectric point (pI) and molecular mass (Mr) with the theoretical pI and Mr. Proteins can be separated in a 2D-SDS-PAGE gel based on protein isoelectric point (pI) and molecular mass (Mr), and the more abundant proteins will manifest themselves with larger and darker dots in the gel than less abundant proteins. Because theoretical protein pI and Mr. can be easily calculated, and protein abundance can be approximated by predicted translation efficiency, we can do in silico 2D-SDS-PAGE and compare the separation pattern against that in the empirical 2-D gel. Differences between the two suggest posttranslational modifications. This approach is numerically and visually illustrated by analyzing a protein sample from the human gastric pathogen, Helicobacter pylori. Proteomics has four objectives listed in the previous chapter, which also covered one of the objectives, i.e., the identification of proteins in a sample by peptide mass fingerprinting. This chapter focuses on another objective, i.e., the identification of posttranslational modifications (PTMs). There are two broad categories of PTMs: the change in molecular mass and changes in charge. The most straightforward way of identifying these changes is to visualize proteins on an empirical 2D-SDS-PAGE gel and on a theoretical gel. If a protein migrates more slowly than the theoretical expectation, then it has gained additional functional groups. If a protein has shifted its position to the left of its expected position along the isoelectric focusing dimension, then it has lost positive charges, e.g., acetylation of the amino group, or gained negative charges, e.g., phosphorylation of some of the amino acid residues. Many 2D-SDS-PAGE experiments have been done in the past, with proteins identified through various means, including the peptide mass fingerprinting method covered in the previous chapter. The gel pictures have been hosted in various databases, e.g., Proteome 2D-PAGE Database (Jungblut and Pleissner 2014). These databases, while being truly a treasure trove, represent the most underutilized resource in biology. I hope that this chapter will rekindle the interest among biologists in PTMs.