Prioritization of Chemicals Based on Chemoinformatic Analysis-Reference-Cited by-同舟云学术

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Prioritization of Chemicals Based on Chemoinformatic Analysis

Published:2016 Issue: Volume: Page:1-33
ISSN:
Container-title:Handbook of Computational Chemistry
language:
Short-container-title:

Author:

Gramatica Paola

Publisher

Springer Netherlands

Link

http://link.springer.com/content/pdf/10.1007/978-94-007-6169-8_58-1

Reference100 articles.

1. Arnot, J. A., Brown, T. N., Wania, F., et al. (2012). Prioritizing chemicals and data requirements for screening-level exposure and risk assessment. Environmental Health Perspectives, 120, 1565–1570. doi:10.1289/ehp.1205355.

2. Asikainen, A. H., Ruuskanen, J., & Tuppurainen, K. A. (2004). Consensus kNN QSAR: A versatile method for predicting the estrogenic activity of organic compounds in silico. A comparative study with five estrogen receptors and a large, diverse set of ligands. Environmental Science and Technology, 38, 6724–6729. doi:10.1021/es049665h.

3. Asikainen, A., Kolehmainen, M., Ruuskanen, J., & Tuppurainen, K. (2006). Structure-based classification of active and inactive estrogenic compounds by decision tree, LVQ and kNN methods. Chemosphere, 62, 658–673. doi:10.1016/j.chemosphere.2005.04.115.

4. Balaban, A. T. (1983). Topological indices based on topological distances in molecular graphs. Pure and Applied Chemistry, 55, 199–206.

5. Bhhatarai, B., & Gramatica, P. (2010). Per- and polyfluoro toxicity (LC50 Inhalation) study in rat and mouse using QSAR modeling. Chemical Research in Toxicology, 23, 528–539. doi:10.1021/tx900252h.

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1. Principles of QSAR Modeling;International Journal of Quantitative Structure-Property Relationships;2020-07

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