Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Quantitative Structure-Activity Relationship Modeling for the Prediction of Fish Toxicity Lethal Concentration on Fathead Minnow Subject The topic of the resource Aquatic Toxicity; Fathead Minnow; LC50; Lethal Concentrations; Pimephales promelas; QSAR Description An account of the resource As there has been a rise in the usage of in silico approaches, for assessing the risks of harmful chemicals upon animals, more researchers focus on the utilization of Quantitative Structure Activity Relationship models. A number of machine learning algorithms link molecular descriptors that can infer chemical structural properties associated with their corresponding biological activity. Efficient and comprehensive computational methods which can process huge set of heterogeneous chemical datasets are in demand. In this context, this study establishes the usage of various machine learning algorithms in predicting the acute aquatic toxicity of diverse chemicals on Fathead Minnow (Pimephales promelas). Sample drive approach is employed on the train set for binning the data so that they can be located in a domain space having more similar chemicals, instead of using the dataset that covers a wide range of chemicals at the entirety. Here, bin wise best learning model and subset of features that are minimally required for the classification are found for further ease. Several regression methods are employed to find the estimation of toxicity LC50 value by adopting several statistical measures and hence bin wise strategies are determined. Through experimentation, it is evident that the proposed model surpasses the other existing models by providing an R2 of 0.8473 with RMSE 0.3035 which is comparable. Hence, the proposed model is competent for estimating the toxicity in new and unseen chemical. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. Creator An entity primarily responsible for making the resource Kavitha R.; Guru D.S. Source A related resource from which the described resource is derived Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , Vol-15310 LNCS, pp. 34-46. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-78192-6_3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-78192-6_3</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212518791&amp;doi=10.1007%2F978-3-031-78192-6_3&amp;partnerID=40&amp;md5=637834c2aa73ee63497707f407787757" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212518791&amp;doi=10.1007%2f978-3-031-78192-6_3&amp;partnerID=40&amp;md5=637834c2aa73ee63497707f407787757</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 3029743; ISBN: 978-303178191-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kavitha R., Department of Data Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560 029, India; Guru D.S., Department of Studies in Computer Science, University of Mysore, Karnataka, Mysuru, 570 006, India