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-Led by Principal Investigator Corbin Jones, professor of biology in the College of Arts and Sciences, AIxB has the potential to revolutionize AI for biosciences by taking a fresh look at AI technologies through the lens of biology.
+Biology and Artificial Intelligence (AI) have long had a symbiotic relationship. Some early efforts in AI were modeled on biological processes, most notably genetic algorithms and neural networks; but as the applications of AI have expanded, the overt relationship between the ideas behind Biology and AI has been obscured. Our teams seeks to re-invigorate this symbiosis by employing innovative AI approaches that incorporate the unifying principles of biology to tackle a challenging biological problems. For instance, scientists have tried for over a century to decipher how the information encoded in the DNA of an organism gives rise to its consequential constellation of observable traits. This “genotype to phenotype” problem has been painstakingly investigated by manipulating individual genes—using natural variation, chemical or radiation induced mutation, or editing with CRISPR and related genome editing technologies—and investigating the resultant phenotypes. While direct and fruitful, this approach is slow and does not scale well. Recently, researchers have poured data from genomes, transcriptomes, proteomes, and the like into databases and other repositories, with the hope that these massive datasets would elucidate how genotype defines phenotype. While rich, these datasets have become impossible for most biologists to synthesize and interrogate fully. AI enables scientists to process unprecedented amounts of data and detect patterns and phenomena that might never have been spotted by the human eye. However, the common approaches use are often black boxes that can describe the data or its patterns but fail to provide biological or mechanistic insights. 
+Our goal is to jointly address two challenges: developing a better understanding of how to apply AI to biological problems by inventing and implementing novel AI approaches that both predict and explain the relationships revealed and to uses the novel biological mechanisms and patterns discovered to inspire new approaches to AI. Led by Principal Investigator Corbin Jones, professor of biology in the College of Arts and Sciences, AIxB has the potential to revolutionize AI for biosciences by taking a fresh look at AI technologies through the lens of biology.