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Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole\u2010organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high\u2010throughput imaging and quantitative phenotyping to measure\n                    <jats:italic>Caenorhabditis<\/jats:italic>\n                    <jats:italic>elegans<\/jats:italic>\n                    behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode\u2010of\u2010action labels. High\u2010throughput imaging and automated phenotyping could therefore accelerate mode\u2010of\u2010action discovery in invertebrate\u2010targeting compound development and help to refine mode\u2010of\u2010action categories.\n                  <\/jats:p>","DOI":"10.15252\/msb.202110267","type":"journal-article","created":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T03:39:20Z","timestamp":1621913960000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Behavioral fingerprints predict insecticide and anthelmintic mode of action"],"prefix":"10.1038","volume":"17","author":[{"given":"Adam","family":"McDermott\u2010Rouse","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eleni","family":"Minga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1046-9606","authenticated-orcid":false,"given":"Ida","family":"Barlow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luigi","family":"Feriani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philippa H","family":"Harlow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony J","family":"Flemming","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1324-8764","authenticated-orcid":false,"given":"Andr\u00e9 E X","family":"Brown","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,5,25]]},"reference":[{"key":"BFMSB202110267_CR1","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.neuron.2014.09.005","volume":"84","author":"DJ Anderson","year":"2014","unstructured":"Anderson DJ, Perona P (2014) Toward a science of computational ethology. 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