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pretty_name: Assay-Interfering-Compounds Finder
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# Boldini2024 (
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17 Datasets that are used to employ Minimum Variance Sampling Analysis (MVS-A) to find Assay Interfering Compounds (AIC) in High Throughput Screening data.
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In this study, they present the first data-driven approach to simultaneously detect assay interferents and prioritize true bioactive compounds.
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Their method enables false positive and true positive detection without relying on prior screens or assay interference mechanisms, making it applicable to any high throughput screening campaign.
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pretty_name: Assay-Interfering-Compounds Finder
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# Boldini2024 (Assay-Interfering-Compounds Finder)
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17 Datasets that are used to employ Minimum Variance Sampling Analysis (MVS-A) to find Assay Interfering Compounds (AIC) in High Throughput Screening data.
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In this study, they present the first data-driven approach to simultaneously detect assay interferents and prioritize true bioactive compounds.
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Their method enables false positive and true positive detection without relying on prior screens or assay interference mechanisms, making it applicable to any high throughput screening campaign.
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