In this work we have studied three different levels of biological networks. First we analyze the potential of a new technique that allows fast DNA sequencing of genomes that have previously been sequenced or have a close relative genome to be used as a reference for the montage of the DNA. We showed that different analyses can be made with the data provided by this technique even though the coverage is much lower than previous, but slower, machines. In the second level, we analyze how gene networks evolve and generate complexity. We study the different mechanisms and evaluate the role of mating in creating and preserving viable organisms with complex networks. Thirdly we work with evolutionary landscapes and how parasites can evade targeting drugs. We analyze all possible paths to resistance and show that real parasites have to rely on very additive networks to be able to evade drug resistance, which is not expected from randomly generated landscapes. Life has a unique way to evolve.