Dener Ribeiro

Summary Gene regulatory networks (GRN) are dynamic models in time and space. These models are used to predict diseases and in drugs research. GRN models are discrete, and Boolean graphs can efficiently represent them. However, GRN algorithms explore a large solution space with high computational complexity. This work proposes efficient FPGA-based accelerators to implement two GRN algorithms: attractor computation and Derrida plot.