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Although a number of ML-based studies have been published, most studies only report fragments of the wider range of bioactivities wherein each model typically focuses on a particular disease. This study introduces FP-MAP, an extensive atlas of fingerprint-based prediction models that covers a diverse range of activities including neglected tropical diseases (caused by viral, bacterial and parasitic pathogens) as well as other targets implicated in diseases such as Alzheimer\u2019s. To arrive at the best predictive models, performance of \u22484,000 classification\/regression models were evaluated on different bioactivity data sets using 12 different molecular fingerprints. The best performing models that achieved test set AUC values of 0.62\u20130.99 have been integrated into an easy-to-use graphical user interface that can be downloaded from <jats:ext-link>https:\/\/gitlab.com\/vishsoft\/fpmap<\/jats:ext-link>.<\/jats:p>","DOI":"10.3389\/fchem.2023.1239467","type":"journal-article","created":{"date-parts":[[2023,8,16]],"date-time":"2023-08-16T07:15:37Z","timestamp":1692170137000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["FP-MAP: an extensive library of fingerprint-based molecular activity prediction tools"],"prefix":"10.3389","volume":"11","author":[{"given":"Vishwesh","family":"Venkatraman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,8,15]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"107766","DOI":"10.1016\/j.compbiolchem.2022.107766","article-title":"EBOLApred: a machine learning-based web application for predicting cell entry inhibitors of the ebola virus","volume":"101","author":"Adams","year":"2022","journal-title":"Comput. 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