Practical Design and Implementation of Virtual Chatbot Assistants for Bioinformatics Based on a NLU Open Framework

Abstract

In this work, we describe the implementation of an infrastructure of conversational chatbots by using natural language processing and training within the Rasa framework. We use this infrastructure to create a chatbot assistant for the users of a bioinformatics suite. This suite provides a customized interface solution for omic pipelines and workflows, and it is named GPRO. The infrastructure has also been used to build another chatbot for a Laboratory Information Management System (LIMS). The two chatbots (namely, Genie and Abu) have been built on an open framework that uses natural language understanding (NLU) and machine learning techniques to understand user queries and respond to them. Users can seamlessly interact with the chatbot to receive support on navigating the GPRO pipelines and workflows. The chatbot provides a bridge between users and the wealth of bioinformatics knowledge available online.

Keywords

• natural language processing and understanding
• virtual assistants
• open frameworks
• bioinformatics suites