Special Issue "Advancing Cheminformatics—A Theme Issue in Honor of Professor Jürgen Bajorath"
Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 15361
Interests: mathematics and computer science; cheminformatics; virtual screening methods; algorithmic methods; mathematical, statistical, and data mining approaches for chemoinformatic questions
In the last 15–20 years, Prof. Dr. Jürgen Bajorath has been one of the leading figures in cheminformatics and in chemical information sciences. With over 700 publications to his name, he has shaped the field in many ways. His research focuses on the development of methods for the analysis and prediction of bioactive molecules and their application in pharmaceutical research. His publications cover a wide range of areas, including the development of methods and algorithms for:
- molecular similarity analysis and computer-based hit and lead identification;
- analysis, characterization, and visualization of systematical structure–activity relationships;
- analysis of lead optimization efforts;
- analysis of big data in medicinal chemistry.
Furthermore, Prof. Bajorath has made substantial contributions in the application of machine learning, data mining, and visualization techniques to the field.
Since 2004, Prof. Bajorath has served as the chair of Life Science Informatics at the Bonn-Aachen International Centers for Information Technology, which is associated with the University of Bonn, and where 30 PhD students have graduated successfully under his supervision in the past 16 years.
In 2015 he received the Herman-Skolnik Award and in 2018 the National Award for Computers in Chemical and Pharmaceutical Research from the American Chemical Society. In 2016, he received the inaugural Fujita Award of the Hansch-Fujita Foundation.
Considering his outstanding accomplishments, we would like to dedicate a Special Issue in honor of Prof. Jürgen Bajorath with a collection of reviews and original articles from his research areas.
Dr. Martin Vogt
Manuscript Submission Information
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- molecular similarity
- virtual screening
- structure–activity relationship
- lead optimization
- big data
- machine learning
- data mining