Researchers from the University of Jena, the Westphalian University of Applied Sciences and the University of Chemistry and Technology Prague have developed a platform that uses artificial neural networks to translate chemical structural formulae into machine-readable form.
can be automatically fed into databases. Until now, this had to be done literally by hand and was time-consuming. In the current issue of, the team led by Prof. Christoph Steinbeck and Prof. Achim Zielesny presents the latest version of their tool, DECIMER.ai, which researchers can use worldwide.are constructed, i.e., which atoms they consist of, how these are arranged spatially and how they are connected.
And that is precisely what can be done using the artificial intelligence tool DECIMER, developed by the team led by Steinbeck and his colleague Zielesny from the Westphalian University of Applied Sciences. DECIMER stands for"deep learning for chemical image recognition." It is an open-source platform that is freely available to everyone on the Internet and can be used in a standard web browser.
In this way, the chemical structural formula for the caffeine molecule becomes the machine-readable structure code CN1C=NC2=C1CNN2C)C. This can then be uploaded directly into a database and linked to further information on the molecule. Steinbeck and Zielesny came up with the idea of developing an AI tool for decoding chemical images a few years ago. The two chemists were interested the development of AI methods in connection with the millennia-old AsianGo. In 2016, together with millions of people around the world, they watched the spectacular tournament between the best Go player at the time, the South Korean Lee Sedol, and the computer software AlphaGo, which the machine won 4:1.
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