Editorial: Charting Chemical Space: Challenges and Opportunities for Artificial Intelligence and Machine Learning
✍ Scribed by Pierre Baldi; Klaus-Robert Müller; Gisbert Schneider
- Publisher
- Wiley (John Wiley & Sons)
- Year
- 2011
- Tongue
- English
- Weight
- 150 KB
- Volume
- 30
- Category
- Article
- ISSN
- 1868-1743
No coin nor oath required. For personal study only.
✦ Synopsis
In spite of its central role and position between physics and biology, chemistry has remained in a somewhat backward state of informatics development compared to its two close scientific relatives, primarily for historical reasons. Computers, open public databases, and large collaborative projects have become the pervasive hallmark of research in physics and biology, but are still at a comparably early stage of development in chemistry. Recently, however, data banks containing millions of small molecules have become freely available, and large repositories of chemical reactions have been developed. These data create a wealth of fascinating informatics and machine learning challenges to efficiently store, search, and predict the physical, chemical, and biological properties of small molecules and reactions and chart "chemical space". Profound understanding of its structure and appropriate computational models will have significant scientific and technological impact.