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Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)
This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchm...
Gorde:
| Argitaratua izan da: | Methods Mol Biol |
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| Egile Nagusiak: | , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2015
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4510302/ https://ncbi.nlm.nih.gov/pubmed/25502380 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-1-4939-2239-0_9 |
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