An innovative machine learning-based QSAR approach for prediction and structural analysis of novel/repurposed acid ceramidase (ASAH1) inhibitors for glioblastoma therapy
Crossref DOI link: https://doi.org/10.1007/s11030-025-11281-9
Published Online: 2025-07-19
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Sajal, Harshit
Mishra, Seema
Text and Data Mining valid from 2025-07-19
Version of Record valid from 2025-07-19
Article History
Received: 14 April 2025
Accepted: 25 June 2025
First Online: 19 July 2025
Declarations
:
: The authors declare no competing interests.