Identification of Novel Antibacterials Using Machine Learning Techniques

Many pharmaceutical companies are avoiding the development of novel antibacterials due to a range of rational reasons and the high risk of failure. However, there is an urgent need for novel antibiotics especially against resistant bacterial strains. Available in silico models suffer from many drawb...

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Detalles Bibliográficos
Autores principales: Ivanenkov, Yan A., Zhavoronkov, Alex, Yamidanov, Renat S., Osterman, Ilya A., Sergiev, Petr V., Aladinskiy, Vladimir A., Aladinskaya, Anastasia V., Terentiev, Victor A., Veselov, Mark S., Ayginin, Andrey A., Kartsev, Victor G., Skvortsov, Dmitry A., Chemeris, Alexey V., Baimiev, Alexey Kh., Sofronova, Alina A., Malyshev, Alexander S., Filkov, Gleb I., Bezrukov, Dmitry S., Zagribelnyy, Bogdan A., Putin, Evgeny O., Puchinina, Maria M., Dontsova, Olga A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Pharmacology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719509/
https://www.ncbi.nlm.nih.gov/pubmed/31507413
http://dx.doi.org/10.3389/fphar.2019.00913

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719509/
https://www.ncbi.nlm.nih.gov/pubmed/31507413
http://dx.doi.org/10.3389/fphar.2019.00913

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