Developing an AI research assistant for biotechnological researches using deep learning approaches. To teach the network we will use the detailed bio-information data- and knowledge base of our biotechnological research group.

The so called deep learning network systems are getting more and more attention in nowadays AI development projects. These networks with enough datasets and knowledge base to teach them are capable of reproducing the given intelligent processes. There are many such expert systems which are based on deep learning, like voice recognition, sentence interpreting, language recognition, medical and diagnostic expert systems, chess and other strategic play systems.

Because its fast growing development the presently available data- and knowledge quantity available in biotechnology, especially in genetic researches are reach enough to create a deep learning based AI research assistant. This would help to further accelerate these researches and to improve its precision. By utilising more advanced methods developed by our theoretical group this AI expert system will be capable of modelling and checking genetically controlled biochemical processes.