PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery

The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and p...

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Bibliographic Details
Main Author:	Muzammil Kabier (21028487) (author)
Other Authors:	Nicola Gambacorta (9514363) (author), Fulvio Ciriaco (5569355) (author), Fabrizio Mastrolorito (14264646) (author), Sunil Kumar (102321) (author), Bijo Mathew (3711802) (author), Orazio Nicolotti (168458) (author)
Published:	2025
Subjects:	Genetics Pharmacology Biotechnology Science Policy Space Science Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified personal optimization software new bioactive compounds customizable filtering settings integrate models effortlessly classification models along unifying data preparation curated bioactivity data given new fuel online qsar ), trained qsar models https :// github based applications makes screening large volumes portable qsar models qsar models based applications pharmacological data large amounts also given qsar model qsar approaches wide audience ubuntu 22 streamlit cloud skill levels seamless integration researchers irrespective rationale design operating systems molecular fingerprints model generation latest version intuitive workflow high volume gathering high empowering users drug design chembl database automatically linked 17 types 04 distro
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PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery

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