Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task
(2022)
Journal Article
Kok, Y. E., Woodward, S., Özcan, E., & Torres Torres, M. (2022). Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task. Molecular Informatics, 41(12), Article 2200068. https://doi.org/10.1002/minf.202200068
Chirality, the ability of some molecules to exist as two non-superimposable mirror images, profoundly influences both chemistry and biology. Advances in deep learning enable the automatic recognition of chemical structure diagrams, however, studies o... Read More about Identifying Chirality in Line Drawings of Molecules Using Imbalanced Dataset Sampler for a Multilabel Classification Task.