Abstract
In this chapter, we present and discuss the state of the art in image analysis tools for nanomaterials’ toxicology. These tools employ novel computational techniques and can contribute to the in silico characterization of materials in complex matrices and their toxicity assessment, by way of recognizing malformations in Daphnia magna. The tools presented were developed using well-established computational platforms and complemented with an user-friendly interface to allow even users without no informatics background to easily get acquainted with them and facilitating their routine use. The tools are freely available as cloud web-applications, while it is also possible to use Application Programming Interfaces (APIs) to integrate the tools into external platforms or to download a containerized Docker application for local deployment. By the end of the chapter, readers will have a clear overview of the functionalities and abilities of the presented tools and the potential added value they offer in terms of working hours, experimental cost, and research outputs for in silico evaluation of nanomaterials toxicity as part of an integrated approach to testing and assessment.
Original language | English |
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Title of host publication | Chemometrics and Cheminformatics in Aquatic Toxicology |
Editors | Kunal Roy |
Publisher | Wiley |
Chapter | 28 |
Pages | 547-564 |
Number of pages | 18 |
ISBN (Electronic) | 9781119681397, 9781119681601 |
ISBN (Print) | 9781119681595 |
DOIs | |
Publication status | Published - Jan 2022 |
Bibliographical note
Publisher Copyright:© 2022 John Wiley and Sons, Inc.
Keywords
- artificial intelligence
- cheminformatics
- Daphnia magna
- deep learning
- DeepDaph
- ecotoxicology
- Enalos Cloud Platform
- engineered nanomaterials
- image analysis
- nanoinformatics
- NanoXtract
ASJC Scopus subject areas
- General Chemistry
- Pharmacology, Toxicology and Pharmaceutics(all)