{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T11:44:00Z","timestamp":1767181440624,"version":"build-2238731810"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013337","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T00:00:00Z","timestamp":1753920000000}}],"reference-count":33,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T00:00:00Z","timestamp":1753660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"funder":[{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["P42 ES016465"],"award-info":[{"award-number":["P42 ES016465"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["R35 ES031709"],"award-info":[{"award-number":["R35 ES031709"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["P30 ES030287"],"award-info":[{"award-number":["P30 ES030287"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>\n                    Though chemical exposures are known to potentially have negative impacts on health, including contributing to chronic diseases such as cancer, the quantitative contribution of risk is not fully understood for every chemical. A commonly used approach to quantify levels of risk is to measure the proportion of organisms (such as a total number of zebrafish on a plate or mice in a cage) with abnormal behavioral responses or morphology at increasing concentrations of chemical exposure. A particular challenge with processing the proportional data from these assays is the appropriate estimation of chemical concentration levels that result in malformations or acute toxicity, as these values typically vary between experimental measurements. The recommended approach by the Environmental Protection Agency (EPA) is to fit benchmark dose curves with specific filters and model fitting steps, which are crucial to properly processing the proportional data. Several tools exist for the fitting of benchmark dose response curves, but none are standalone Python libraries built to process both morphological and behavioral data as proportions with all the EPA recommended filters, filter parameters, models, and model parameters. Thus, here we present the benchmark dose response curve (\n                    <jats:italic>bmdrc<\/jats:italic>\n                    ) Python library, which was built to closely follow these EPA guidelines with helpful visualizations of filters and fitted model curves, and reports for reproducibility purposes.\n                    <jats:italic>\n                      <jats:italic>bmdrc<\/jats:italic>\n                    <\/jats:italic>\n                    is open-source and has demonstrated utility as a support package to an existing web portal for information on chemicals (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/srp.pnnl.gov\" xlink:type=\"simple\">https:\/\/srp.pnnl.gov<\/jats:ext-link>\n                    ). Our package will support any toxicology analysis where the response is a proportional value at increasing levels of a concentration of a chemical or chemical mixture.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1013337","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T17:50:53Z","timestamp":1753725053000},"page":"e1013337","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["bmdrc: Python package for quantifying phenotypes from chemical exposures with benchmark dose modeling"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5737-7173","authenticated-orcid":true,"given":"David J.","family":"Degnan","sequence":"first","affiliation":[]},{"given":"Lisa M.","family":"Bramer","sequence":"additional","affiliation":[]},{"given":"Lisa","family":"Truong","sequence":"additional","affiliation":[]},{"given":"Robyn L.","family":"Tanguay","sequence":"additional","affiliation":[]},{"given":"Sara M.","family":"Gosline","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4696-5396","authenticated-orcid":true,"given":"Katrina M.","family":"Waters","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2025,7,28]]},"reference":[{"issue":"2","key":"pcbi.1013337.ref001","first-page":"154","article-title":"Environmental toxins and the impact of other endocrine disrupting chemicals in women\u2019s reproductive health","volume":"23","author":"MJ Piazza","year":"2019","journal-title":"JBRA Assist Reprod"},{"issue":"3","key":"pcbi.1013337.ref002","first-page":"229","article-title":"Synopsis polycyclic aromatic hydrocarbons (PAHs) in soil\u2014a review","volume":"163","author":"W Wilcke","year":"2000","journal-title":"JPNSS"},{"key":"pcbi.1013337.ref003","doi-asserted-by":"crossref","first-page":"133971","DOI":"10.1016\/j.scitotenv.2019.133971","article-title":"Comprehensive review of polycyclic aromatic hydrocarbons in water sources, their effects and treatments","volume":"696","author":"A Mojiri","year":"2019","journal-title":"Sci Total Environ"},{"issue":"13","key":"pcbi.1013337.ref004","doi-asserted-by":"crossref","first-page":"2895","DOI":"10.1016\/j.atmosenv.2007.12.010","article-title":"Atmospheric polycyclic aromatic hydrocarbons: source attribution, emission factors and regulation","volume":"42","author":"K Ravindra","year":"2008","journal-title":"Atmos Environ"},{"issue":"6","key":"pcbi.1013337.ref005","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1073\/pnas.1618475114","article-title":"Global long-range transport and lung cancer risk from polycyclic aromatic hydrocarbons shielded by coatings of organic aerosol","volume":"114","author":"M Shrivastava","year":"2017","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"23","key":"pcbi.1013337.ref006","doi-asserted-by":"crossref","first-page":"13807","DOI":"10.1021\/acs.est.5b00800","article-title":"Relative Influence of Trans-Pacific and Regional Atmospheric Transport of PAHs in the Pacific Northwest, U.S","volume":"49","author":"S Lafontaine","year":"2015","journal-title":"Environ Sci Technol"},{"issue":"14","key":"pcbi.1013337.ref007","doi-asserted-by":"crossref","first-page":"5196","DOI":"10.1021\/es800453n","article-title":"Atmospheric transport and outflow of polycyclic aromatic hydrocarbons from China","volume":"42","author":"C Lang","year":"2008","journal-title":"Environ Sci Technol"},{"issue":"17","key":"pcbi.1013337.ref008","doi-asserted-by":"crossref","first-page":"6519","DOI":"10.1021\/es800511x","article-title":"Influence of Asian and Western United States agricultural areas and fires on the atmospheric transport of pesticides in the Western United States","volume":"42","author":"T Primbs","year":"2008","journal-title":"Environ Sci Technol"},{"issue":"9","key":"pcbi.1013337.ref009","doi-asserted-by":"crossref","first-page":"1172","DOI":"10.1080\/10473289.1991.10466911","article-title":"Making cleanup decisions at hazardous waste sites: the clean sites approach","volume":"41","author":"DJ Sarno","year":"1991","journal-title":"J Air Waste Manage Assoc"},{"key":"pcbi.1013337.ref010","unstructured":"EPA. 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