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QSAR without bordersстатья
Статья опубликована в высокорейтинговом журнале
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 17 июля 2020 г.
- Авторы: Muratov Eugene N., Jürgen Bajorath, Sheridan Robert P., Tetko Igor V., Dmitry Filimonov, Vladimir Poroikov, Oprea Tudor I., Baskin Igor I., Alexandre Varnek, Adrian Roitberg, Olexandr Isayev, Stefano Curtalolo, Denis Fourches, Yoram Cohen, Alan Aspuru-Guzik, Winkler David A., Dimitris Agrafiotis, Artem Cherkasov, Alexander Tropsha
- Журнал: Chemical Society Reviews
- Том: 49
- Год издания: 2020
- Издательство: Royal Society of Chemistry
- Местоположение издательства: United Kingdom
- Первая страница: 3525
- Последняя страница: 3564
- DOI: 10.1039/D0CS00098A
- Аннотация: Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure–activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust datadriven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.
- Добавил в систему: Баскин Игорь Иосифович