In an effort to make DNA sequencing more accessible and affordable, Oxford Nanopore Technologies developed the MinION: A portable cellphone sized DNA sequencing device. Translating the information from this device to a nucleotide sequence is called basecalling, and is done with the aid of artificial neural networks. In this thesis, we accelerate a neural network using the concept of Dataflow programming. The result is a complete basecalling application that relies on an FPGA based platform to run the compute intensive parts. We achieve up to 1.51x speedup over a high-end server with two Intel Xeon Processors, with a rate of 57,040 bases per second. In addition, our implementation uses up to 90.27\% less energy compared to the original implementation.