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Deciding when to stop: efficient experimentation to learn to predict drug-target interactions
BACKGROUND: Active learning is a powerful tool for guiding an experimentation process. Instead of doing all possible experiments in a given domain, active learning can be used to pick the experiments that will add the most knowledge to the current model. Especially, for drug discovery and developmen...
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| Gepubliceerd in: | BMC Bioinformatics |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
BioMed Central
2015
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4495685/ https://ncbi.nlm.nih.gov/pubmed/26153434 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-015-0650-9 |
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