Practical application of the Average Information Content Maximization (AIC-MAX) algorithm: selection of the most important structural features for serotonin receptor ligands

The Average Information Content Maximization algorithm (AIC-MAX) based on mutual information maximization was recently introduced to select the most discriminatory features. Here, this methodology was applied to select the most significant bits from the Klekota-Roth fingerprint for serotonin recepto...

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Detalles Bibliográficos
Autores principales: Warszycki, Dawid, Śmieja, Marek, Kafel, Rafał
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5438429/
https://www.ncbi.nlm.nih.gov/pubmed/28185036
http://dx.doi.org/10.1007/s11030-017-9729-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5438429/
https://www.ncbi.nlm.nih.gov/pubmed/28185036
http://dx.doi.org/10.1007/s11030-017-9729-8

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