Fragment-similarity-based QSAR (FS-QSAR) algorithm for ligand biological activity predictions
Author:
Publisher
Informa UK Limited
Subject
Drug Discovery,Molecular Medicine,General Medicine,Bioengineering
Link
http://www.tandfonline.com/doi/pdf/10.1080/1062936X.2011.569943
Reference26 articles.
1. QSAR and 3D QSAR in drug design Part 1: methodology
2. Fragment-based QSAR: perspectives in drug design
3. 3D-QSAR Studies of Arylpyrazole Antagonists of Cannabinoid Receptor Subtypes CB1 and CB2. A Combined NMR and CoMFA Approach
4. Top-Priority Fragment QSAR Approach in Predicting Pesticide Aquatic Toxicity
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1. Biological Activity Predictions of Ligands Based on Hybrid Molecular Fingerprinting and Ensemble Learning;ACS Omega;2023-02-01
2. Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications;The AAPS Journal;2018-04-09
3. In Silico Chemogenomics Knowledgebase and Computational System Neuropharmacology Approach for Cannabinoid Drug Research;Neuropathology of Drug Addictions and Substance Misuse;2016
4. Newer QSAR Techniques;Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment;2015
5. Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR);Methods in Molecular Biology;2014-11-21
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