Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Structure-activity relationship analysis of rat mammary carcinogens.

Chemical research in toxicology - 1 Oct 2008

Cunningham Albert R, Moss Shanna T, Iype Seena A, Qian Gefei, Qamar Shahid, Cunningham Suzanne L

Abstract excerpt

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe here the application of the cat-SAR (categorical-SAR) program to two learning sets of rat mammary carcinogens. One set of developed models was based on a comparison of rat mammary carcinogens to rat...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Breast Neoplasms
Share to Carcinogens
Share to Computer Simulation

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Disease Models, Animal

Share to Molecular Structure

Share to Salmonella

Share to Structure-Activity Relationship

Source

Identifiers

PMID: 18759503
DOI: 10.1021/tx8001725

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Structure-activity relationship analysis of rat mammary carcinogens.PMID 18759503Read ↗

Application of the Key Characteristics Framework to Identify Potential Breast Carcinogens Using Publicly Available in Vivo , in Vitro , and in Silico DataSemantic proximity Read ↗

Structure alerts for carcinogenicity, and the Salmonella assay system: a novel insight through the chemical relational databases technology.Semantic proximity Read ↗

Methods for predicting carcinogenic hazards: new opportunities coming from recent developments in molecular oncology and SAR studies.Semantic proximity Read ↗

Categorizing the characteristics of human carcinogens: a need for specificitySemantic proximity Read ↗

Chemical Carcinogenesis of Rat and Mouse Mammary GlandsSemantic proximity Read ↗

A Deep-Learning Approach for Identifying Prospective Chemical HazardsSemantic proximity Read ↗

Alternatives to the carcinogenicity bioassay:<i>in silico</i>methods, and the<i>in vitro</i>and<i>in vivo</i>mutagenicity assaysSemantic proximity Read ↗

Identification of the Structural Requirements for Mutagenicity by Incorporating Molecular Flexibility and Metabolic Activation of Chemicals I: TA100 ModelSemantic proximity Read ↗

IARC Workshop on the Key Characteristics of Carcinogens: Assessment of End Points for Evaluating Mechanistic Evidence of Carcinogenic HazardsSemantic proximity Read ↗

Prediction of Micronucleus Assay Outcome using in Vivo Activity Data and Molecular Structure FeaturesSemantic proximity Read ↗

Use of the bacterial reverse mutation assay to predict carcinogenicity of N-nitrosamines.Semantic proximity Read ↗

Potential of ToxCast Data in the Safety Assessment of Food ChemicalsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.