Volume 95 Issue 4 | pp. 33-34
Issue Date: January 23, 2017

Cover Stories: New directions for machine learning

Chemists turn to machine learning to get the most out of data

Publishers and others apply standard artificial intelligence techniques to synthesis planning and education
Department: Science & Technology
Keywords: computational chemistry, physical chemistry, synthesis, green chemistry, medicinal chemistry, Reagents, business, start-ups, informatics, publishing, retrosynthesis

Although chemists are excited by the potential of so-called deep-learning computational tools to make a splash in drug discovery, publishers and others are still looking to squeeze findings out of earlier, less sophisticated versions of these tools. With machine-learning techniques that “teach” themselves with large data sets, they hope to get more out of scientific information, whether in the lab or the classroom.

“It’s about how you make discoveries consumable,” says Conal Thompson, chief technology . . .

To view the rest of this content, please log in with your ACS ID.

Chemical & Engineering News
ISSN 0009-2347
Copyright © American Chemical Society