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Improving the profile of a molecule for the drug-discovery process requires the simultaneous optimization of numerous, often competing objectives. Traditionally, standard chemoinformatics methods ignored this problem and focused on the sequential optimization of each single biological or chemical property (ie, a single objective). This approach, known as single-objective optimization (SOOP), strives to discover a single optimal solution to the optimization problem. Implicitly, SOOP-baseddoi:10.5281/zenodo.2555799 fatcat:r4d75kodwjatppw2z4yohbdsva