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Integrated biomarker approach strongly explaining in vivo sub-lethal acute toxicity of butachlor on Labeo rohita.

Comparative biochemistry and physiology. Toxicology & pharmacology : CBP
Butachlor herbicide belongs to the family of chloroacetanilide group, widely used for control of grass and broadleaf weeds in paddy fields however, its repeated application may result in aquatic pollution. Butachlor residue has been detected in aquat...

Classification of collective behavior: a comparison of tracking and machine learning methods to study the effect of ambient light on fish shoaling.

Behavior research methods
Traditional approaches for the analysis of collective behavior entail digitizing the position of each individual, followed by evaluation of pertinent group observables, such as cohesion and polarization. Machine learning may enable considerable advan...

Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm.

SAR and QSAR in environmental research
Large worldwide use of chemicals has caused great concern about their possible adverse effects on human health, flora and fauna. Increased production of new chemicals has also increased demand for their risk assessment. Traditionally, results from an...

Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.

Briefings in bioinformatics
Although a wide variety of machine learning (ML) algorithms have been utilized to learn quantitative structure-activity relationships (QSARs), there is no agreed single best algorithm for QSAR learning. Therefore, a comprehensive understanding of the...

In silico prediction of chemical aquatic toxicity by multiple machine learning and deep learning approaches.

Journal of applied toxicology : JAT
Fish is one of the model animals used to evaluate the adverse effects of a chemical exposed to the ecosystem. However, its low throughput and relevantly high expense make it impossible to test all new chemicals in manufacture. Hence, using in silico ...

Construction of chub mackerel (Scomber japonicus) fishing ground prediction model in the northwestern Pacific Ocean based on deep learning and marine environmental variables.

Marine pollution bulletin
Accurate prediction of the central fishing grounds of chub mackerel is substantial for assessing and managing marine fishery resources. Based on the high-seas chub mackerel fishery statistics and multi-factor ocean remote-sensing environmental data i...

Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives.

International journal of molecular sciences
Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding af...

Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning.

The Science of the total environment
Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquati...