Binary Classification of CNS and PNS Drugs


Цитировать

Полный текст

Открытый доступ Открытый доступ
Доступ закрыт Доступ предоставлен
Доступ закрыт Только для подписчиков

Аннотация

Stable classification predictive models of 626 drugs acting on the central (CNS) and peripheral (PNS) nervous systems were constructed based on linear discriminant analysis, logistic regression, random forest, and support vector machine methods with physicochemical descriptors characterizing the steric factors, electrostatic interactions, and H-bonding features. Internal cross-validations demonstrated that these models possessed satisfactory statistical properties.

Ключевые слова

Об авторах

D. Polianchik

Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences

Автор, ответственный за переписку.
Email: danielpolian@yahoo.com
Россия, Chernogolovka, Moscow Region, 142432

V. Grigor’ev

Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences

Email: danielpolian@yahoo.com
Россия, Chernogolovka, Moscow Region, 142432

G. Sandakov

Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences

Email: danielpolian@yahoo.com
Россия, Chernogolovka, Moscow Region, 142432

A. Yarkov

Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences

Email: danielpolian@yahoo.com
Россия, Chernogolovka, Moscow Region, 142432

S. Bachurin

Department of Biomedicinal Chemistry, Institute of Physiologically Active Substances, Russian Academy of Sciences

Email: danielpolian@yahoo.com
Россия, Chernogolovka, Moscow Region, 142432

O. Raevskii

Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences

Email: danielpolian@yahoo.com
Россия, Chernogolovka, Moscow Region, 142432


© Springer Science+Business Media New York, 2017

Данный сайт использует cookie-файлы

Продолжая использовать наш сайт, вы даете согласие на обработку файлов cookie, которые обеспечивают правильную работу сайта.

О куки-файлах