In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points from which regions encoding proteins start, the so-called translation initiation sites (TIS). This can be modeled as a classification problem. We demonstrate the power of support vector machines (SVMs) for this task, and show how to successfully incorporate biological prior knowledge by engineering an appropriate kernel function.