Support Vector Machine model for hERG inhibitory activities based on the integrated hERG database using descriptor selection by NSGA-II
Abstract Assessing the hERG liability in the early stages of drug discovery programs is important. The recent increase of hERG-related information in public databases enabled various successful applications of machine learning techniques to predict hERG inhibition. However, most of these researches...
Guardado en:
Autores principales: | Keiji Ogura, Tomohiro Sato, Hitomi Yuki, Teruki Honma |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/095e0068fd624717acf73f01c55aecca |
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