Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Mélaine Kuenemann"'
Autor:
Oliver Wieder, Mélaine Kuenemann, Marcus Wieder, Thomas Seidel, Christophe Meyer, Sharon D. Bryant, Thierry Langer
Publikováno v:
Molecules, Vol 26, Iss 20, p 6185 (2021)
The accurate prediction of molecular properties, such as lipophilicity and aqueous solubility, are of great importance and pose challenges in several stages of the drug discovery pipeline. Machine learning methods, such as graph-based neural networks
Externí odkaz:
https://doaj.org/article/99b034c72c334cc1b14a5b97f0dddf56
Autor:
Scarlett Kiyeleko, Sofiane Hocine, Giséle Mautino, Mélaine Kuenemann, Agata Nawrotek, Linda Miallau, Laurent-Michel Vuillard, Olivier Mirguet, Andras Kotschy, Stephen Hanessian
Publikováno v:
Bioorganicmedicinal chemistry letters. 75
We describe the synthesis of a series of 3-t-butyl 5-aminopyrazole p-substituted arylamides as inhibitors of serine-threonine25 (STK25), an enzyme implicated in the progression of non-alcoholic fatty liver disease (NAFLD). Appending a p-N-pyrrolidino
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed826164ebfa1e4b6e3a53c105d52926
https://pubmed.ncbi.nlm.nih.gov/36030002
https://pubmed.ncbi.nlm.nih.gov/36030002
Autor:
Thierry Langer, Thomas Seidel, Oliver Wieder, Christophe Meyer, Mélaine Kuenemann, Marcus Wieder, Sharon D. Bryant
Publikováno v:
Molecules, Vol 26, Iss 6185, p 6185 (2021)
Molecules
Volume 26
Issue 20
Molecules
Volume 26
Issue 20
The accurate prediction of molecular properties, such as lipophilicity and aqueous solubility, are of great importance and pose challenges in several stages of the drug discovery pipeline. Machine learning methods, such as graph-based neural networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::488ee6e90d9dc00a88fa0d9f5fd8f954
Autor:
Oliver Wieder, Arthur Garon, Stefan M. Kohlbacher, Thierry Langer, Thomas Seidel, Mélaine Kuenemann, Pierre Ducrot
As graph neural networks are becoming more and more powerful and useful in the field of drug discovery, many pharmaceutical companies are getting interested in utilizing these methods for their own in-house frameworks. This is especially compelling f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f75a1d5ef900f69a04491f18c1df7fde
https://doi.org/10.1016/j.ddtec.2020.11.009
https://doi.org/10.1016/j.ddtec.2020.11.009