Chemical structure elucidation (CSE) is the process of deducing the structural formula of an unknown chemical compound, with mass spectrometry (MS) and Nuclear Magnetic Resonance (NMR) being the two most widely used techniques. By identifying the fragments produced when the unknown chemical compound breaks up inside the mass spectrometer, and with the complementary data provided by NMR, chemists can infer the structure of the molecule. However, manually carrying out this process is known to be a tedious task in the field of analytical chemistry. This project aims to use machine learning to aid chemists in CSE by predicting the structure of the model given MS, NMR or any other measurable signals.
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Repository containing finalized code for Chemical Structure Elucidation attempts
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