Expressing Biological Problems with Logical Reasoning Languages

Biology represents a very challenging domain that is typically tackled by experts in the field, with few or no interactions with the Web knowledge and rules interoperation community. However, there has been a considerable growth of data regarding biological aspects in the last decades. Moreover, the COVID-19 pandemic has traced an unprecedented point in history, where tons of information have been collected in laboratories worldwide and deposited into open data banks. Inspired by the current needs and backed by a solid knowledge base (our extensional knowledge source) called CoV2K, we propose to express and resolve a series of problems related to the SARS-CoV-2 virus and its interpretation. We formulate our queries as rules in Vadalog (our knowledge representation and reasoning language) and input them to its related logic-based reasoning system. Four cases are presented that allow to explore 1) variants effects and how they are explained in scientific literature; 2) the most typical mutations of a variant; 3) the most likely acquisition of a new mutation by a given variant and the associated reported effects; 4) the most relevant mutations of the virus according to the community. Expressing biological problems using a logic formalism is a major challenge, due to the intrinsic complexity of the domain. The four use cases show that a logical formalism is effective in expressing relevant problems for understanding the current evolution of SARS-CoV-2 variants, an essential aspect of the COVID-19 pandemic.