In our Bioinformatics research we apply methods from computer science and mathematics in medicine and biology. Besides the more traditional approaches in systems and computational biology, which customarily rely on continuous models, e.g., differential equations, we use methods of algorithmic nature. They entail executable models, based on discrete mathematical formalisms like graphs, formal grammars, and automata. Model checking and the other algorithmic techniques that we use, are both alternative and complementary to the traditional approaches. We aim at developing cutting-edge scalable solutions that are able to cope with big data challenges in the context of high-throughput experiments. To this end we capitalize on the capabilities of the state-of-the art parallel technology, like GPUs and multi-core processors.