https://www.selleckchem.com/products/2-d08.html
Open-source data on large scale are the cornerstones for data-driven research, but they are not readily available for polymers. In this work, we build a benchmark database, called PI1M (referring to ∼1 million polymers for polymer informatics), to provide data resources that can be used for machine learning research in polymer informatics. A generative model is trained on ∼12 000 polymers manually collected from the largest existing polymer database PolyInfo, and then the model is used to generate ∼1 million polymers. A new representation
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