Ten years after the idea of hydrophobic cluster analysis (HCA) was conceived and first published, theoretical and practical experience has shown this unconventional method of protein sequence analysis to be particularly efficient and sensitive, especially with families of sequences sharing low levels of sequence identity. This extreme sensitivity has made it possible to predict the functions of genes whose sequence similarities are hardly if at all detectable by current one-dimensional (1D) methods alone, and offers a new way to explore the enormous amount of data generated by genome sequencing. HCA also provides original tools to understand fundamental features of protein stability and folding. Since the last review of HCA published in 1990 [1], significant improvements have been made and several new facets have been addressed. Here we wish to update and summarize this information.