I-Corps: Novel molecule discovery by precisely predicting and modulating human pathology

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The broader impact/commercial potential of this I-Corps project is the development of technology accelerating molecular discovery relevant to meeting urgent challenges in agriculture, environment, energy, and human health/well-being. This system seeks to enable reliable prediction of molecule functions where no similar data has been observed as training data in classic artificial intelligence (AI) algorithms. This solution may provide for the development of new functional molecules such as nitrogen-fixing molecules, compostable plastic, high-efficiency batteries, nanocages for molecular delivery, and safe and effective medicines for incurable diseases. Furthermore, out-of-distribution generalization is a challenge in AI in fundamental research in computer science and mathematics. This system seeks to demonstrate a framework that could be adopted in a broad spectrum of fields beyond the life sciences such as public health, political science, economics, and education.This I-Corps project develops a molecular discovery platform based on studies in machine learning, biophysics, and systems biology. The solution is fueled by omics data generated by next-generation sequencing and high-throughput techniques and powered by state-of-the-art deep learning. The novelty of the approach is its way of integrating data from diverse resources into a unified framework to represent complex biological systems, and enabling machine learning for hypothesis generation. An outcome may be novel therapeutics that have the potential to treat complex diseases such as cancers, neurodegenerative diseases, and substance abuse disorders.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.