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Drug side effect prediction is one of screening methods in drug discovery.
The implications of these methods in drug design will be discussed.
Some of the most popular and successful methods in drug discovery are structure-based.
To describe the use and reporting of interrupted time series methods in drug utilization research.
The importance of wide application of computational methods in drug discovery processes has been extensively reviewed [48, 49].
Our first research goal of big data application is to predict side effect of drug which is one of screening methods in drug discovery.
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Herein, we have compared well-fluorescence and cell-fluorescence methods in drug-resistant human MCF-7 and Hs578T cell lines in order to understand better how variations of cell fluorescence intensity can affect the signals given by the instruments.
All these features of WAC make it a potential method in drug discovery for fragment screening.
Scientific method in drug discovery has centered on generating a hypothesis (target identification) and hypothesis testing (target validation).
Virtual screening (VS) is a widely applied method in drug discovery that is used to predict novel bioactives from large chemical libraries [1 4].
However, the experimental binding mode was reproduced successfully using members of the core ensemble as the docking target, establishing the usefulness of the method in drug design.
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