Starting in 2018, Bo Wang performed a systematic comparison of MAIC against other methods for aggregating experimental results. He found that MAIC performs better than other approaches in most circumstances encountered in genomics and biology. The key factor for deciding on an algorithm is the heterogeneity in information quality between input lists. Because MAIC quantifies this heterogeneity, we were able to modify MAIC to tell users if another algorithm will perform better for their datasets.