Structure-activity relationship studies of chemical mutagens and carcinogens: mechanistic investigations and prediction approaches.
about
Additive SMILES-based carcinogenicity models: Probabilistic principles in the search for robust predictionsPhysicochemical drug properties associated with in vivo toxicological outcomes: a review.Label-free and real-time imaging of dehydration-induced DNA conformational changes in cellular nucleus using second harmonic microscopy.Improving prediction of carcinogenicity to reduce, refine, and replace the use of experimental animals.Metabolic and electrochemical mechanisms of dimeric naphthoquinones cytotoxicity in breast cancer cells.The expanding role of predictive toxicology: an update on the (Q)SAR models for mutagens and carcinogens.Molecular mechanisms underlying chemical liver injury.Predictive models for carcinogenicity and mutagenicity: frameworks, state-of-the-art, and perspectives.Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity.Alternatives to the carcinogenicity bioassay: in silico methods, and the in vitro and in vivo mutagenicity assays.Challenges for computational structure-activity modelling for predicting chemical toxicity: future improvements?Opportunities for an alternative integrating testing strategy for carcinogen hazard assessment?Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities.Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.Antioxidant and antimutagenic potential of Psidium guajava leaf extracts.Prediction of chemical carcinogenicity by machine learning approaches.Prediction of PAH mutagenicity in human cells by QSAR classification.QSAR-assisted virtual screening of lead-like molecules from marine and microbial natural sources for antitumor and antibiotic drug discovery.Re‐evaluation of potassium nitrite (E 249) and sodium nitrite (E 250) as food additivesIn Silico Screening of Chemicals for Genetic Toxicity Using MDL-QSAR, Nonparametric Discriminant Analysis, E-State, Connectivity, and Molecular Property Descriptors.Predictivity and reliability of QSAR models: the case of mutagens and carcinogens.Some findings relevant to the mechanistic interpretation in the case of predictive models for carcinogenicity based on the counter propagation artificial neural network.Quantitative structure-activity relationship modelling of the carcinogenic risk of nitroso compounds using regression analysis and the TOPS-MODE approach.Combined Use of MC4PC, MDL-QSAR, BioEpisteme, Leadscope PDM, and Derek for Windows Software to Achieve High-Performance, High-Confidence, Mode of Action-Based Predictions of Chemical Carcinogenesis in Rodents.Design, synthesis and structure of novel para-quinones and their antibacterial activity.PASS: identification of probable targets and mechanisms of toxicity†Approaches for externally validated QSAR modelling of Nitrated Polycyclic Aromatic Hydrocarbon mutagenicity†
P2860
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P2860
Structure-activity relationship studies of chemical mutagens and carcinogens: mechanistic investigations and prediction approaches.
description
2005 nî lūn-bûn
@nan
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
2005年论文
@zh
2005年论文
@zh-cn
name
Structure-activity relationshi ...... ons and prediction approaches.
@ast
Structure-activity relationshi ...... ons and prediction approaches.
@en
type
label
Structure-activity relationshi ...... ons and prediction approaches.
@ast
Structure-activity relationshi ...... ons and prediction approaches.
@en
prefLabel
Structure-activity relationshi ...... ons and prediction approaches.
@ast
Structure-activity relationshi ...... ons and prediction approaches.
@en
P356
P1433
P1476
Structure-activity relationshi ...... ons and prediction approaches.
@en
P304
P356
10.1021/CR030049Y
P577
2005-05-01T00:00:00Z