Results 281 to 290 of about 2,598,515 (356)

Three pillars for ensuring public access and integrity of chemical databases powering cheminformatics. [PDF]

J Cheminform
Williams AJ, Richard AM.
europepmc   +1 more source

Integrated computational analysis of molecular mechanisms underlying perfluorooctane sulfonic acid induced thyroid toxicity. [PDF]

Sci Rep
Li H, Yu B, Yuan Y, Chen N, Guo H, Zhang H, Zhang Z.   +6 more
europepmc   +1 more source

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Computational Toxicology

Systems Medicine, 2021
Presentation to the American College of Toxicology s online Advanced Comprehensive Toxicology course August 2021Search for CCTE records in EPA s Science Inventory by typing in the title at this link.https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=
Friedemann Schmidt
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Molecular Similarity in Computational Toxicology

Methods in molecular biology, 2018
The concept of chemical similarity has many applications in several fields of cheminformatics. One common use of chemical similarity measurements, based on the principle that similar molecules have similar properties, is in the context of the read-across approach, where estimates of a specific endpoint for a chemical are obtained starting from ...
Matteo Floris, Matteo Floris, Stefania Olla   +2 more
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Computational Toxicology and Drug Discovery

Methods in molecular biology, 2018
The use of computational toxicology methods within drug discovery began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been continuously expanding ever since and the tasks at hand have become more complex.
Glenn J. Myatt, Catrin Hasselgren
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Computational Toxicology

Methods in Molecular Biology, 2018
Computational toxicology played an important role in the ongoing paradigm shift in the field of toxicology. Computation toxicology is inherently a multidisciplinary field, and it comprises the building of models of many different types with different techniques.
S. Thakkar, Weida Tong, Huixiao Hong, R. Perkins   +3 more
semanticscholar   +4 more sources

Machine Learning Methods in Computational Toxicology

Methods in molecular biology, 2018
Various methods of machine learning, supervised and unsupervised, linear and nonlinear, classification and regression, in combination with various types of molecular descriptors, both "handcrafted" and "data-driven," are considered in the context of their use in computational toxicology.
Igor I. Baskin, Igor I. Baskin
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Mind the Gap! A Journey towards Computational Toxicology

Molecular Informatics, 2016
AbstractComputational methods have advanced toxicology towards the development of target‐specific models based on a clear cause‐effect rationale. However, the predictive potential of these models presents strengths and weaknesses. On the good side, in silico models are valuable cheap alternatives to in vitro and in vivo experiments.
Mangiatordi, G. F., Alberga, D., Altomare, C. D., Carotti, A., Catto, M., Cellamare, S., Gadaleta, D., Lattanzi, G., Leonetti, F., Pisani, L., Stefanachi, A., Trisciuzzi, D., Nicolotti, O.   +12 more
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Use of computational toxicology models to predict toxicological points of departure: A case study with triazine herbicides

Birth Defects Research, 2022
Atrazine simazine and propazine, widely used triazine herbicides on food crops and in residential areas, disrupt the neuroendocrine system raising human health concerns.
Marilyn H. Silva, Ryan Kin‐Hin Kwok
semanticscholar   +1 more source

Integration of Computational Toxicology, Toxicogenomics Data Mining, and Omics Techniques to Unveil Toxicity Pathways

ACS Sustainable Chemistry and Engineering, 2021
Growing numbers of synthetic chemicals have potential endocrine-disrupting effects and cause potential ecological and health risks.
Xiaoqing Wang, Fei Li, Jingwen Chen, Chenglong Ji, Huifeng Wu   +4 more
semanticscholar   +1 more source