The potential of organ specific toxicity for predicting rodent carcinogenicity

Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis

Volumn 358, Issue 1, 1996, Pages 37-62

  Lee, Yongwon ^a,d   Buchanan, Bruce G ^a   Klopman, Gilles ^b   Dimayuga, Mario ^b   Rosenkranz, Herbert S ^c  

^a University of Pittsburgh   (United States)

^b CASE WESTERN RESERVE UNIVERSITY   (United States)

^c UNIVERSITY OF PITTSBURGH   (United States)

^d LOCKHEED MARTIN   (United States)

Author keywords

Morphology; Organ specific toxicity; Rodent carcinogenicity; Rule induction

Indexed keywords

ADRENALIN; ALCOHOL; AMPHETAMINE; BENZENE DERIVATIVE; BORIC ACID; CARCINOGEN; COUMARIN; ERYTHROMYCIN STEARATE; FURFURAL; FUROSEMIDE; HYDROCHLOROTHIAZIDE; MALONALDEHYDE; METHYLDOPA; NALIDIXIC ACID; NITROFURAL; NITROFURANTOIN; PARACETAMOL; PENICILLIN V POTASSIUM; PENTAERYTHRITYL TETRANITRATE; PESTICIDE; PHENOL DERIVATIVE; PHENYLBUTAZONE; PHENYLEPHRINE; PIGMENT; TETRACYCLINE; TRIAMTERENE;

ACCURACY; ANIMAL MODEL; ARTICLE; CARCINOGENICITY; CONTROLLED STUDY; DATA BASE; DRUG TOXICITY; DRUG TOXICITY AND INTOXICATION; GENOTOXICITY; INFORMATION PROCESSING; INTERMETHOD COMPARISON; KIDNEY; LIVER; NONHUMAN; PREDICTION; PRIORITY JOURNAL; RISK ASSESSMENT; SALMONELLA; TISSUE SPECIFICITY;

ANIMALIA; RODENTIA; SALMONELLA;

EID: 0030605076     PISSN: 00275107     EISSN: None     Source Type: Journal    
DOI: 10.1016/0027-5107(96)00110-8     Document Type: Article

References (19)

1. Ashby, J. and R.W. Tennant (1991) Definitive relationships among chemical structures, carcinogenicity, and mutagenicity for 301 chemicals tested by the U.S. NTP. Mutation Res., 257, 229-306.
2. Bahler, D. and D.W. Bristol (1993) The induction of rules for predicting chemical carcinogenesis in rodents, in: L. Hunter, J. Shavlik and D. Searls (Eds.), Proceedings of the First International Conference on Intelligent Systems for Molecular Biology, AAAI/MIT Press, Menlo Park, CA, pp. 29-37.
3. Buchanan, B.G. and T.M. Mitchell (1978) Model directed learning of production rules, in: D.A. Waterman and F. Hayes-Roth (Eds.), Pattern Directed Inference Systems, Academic Press, New York, pp. 297-312.
4. Busey, W.M. and Henry, J.F. (1995) Intelligent toxicology prediction system. Toxicologist, 15, 178-179.
5. Clearwater, S.H. and Y. Lee (1993) Use of a learning program for trigger sensitivity studies, in: Proceedings of the Third International Workshop on Software Engineering, Artificial Intelligence and Expert Systems for High Energy and Nuclear Physics, World Scientific, pp. 207-212.
6. Clearwater, S.H. and F.J. Provost (1990) RL4: A tool for knowledge-based induction, in: Proceedings of Tools for Artificial Intelligence 90, IEEE Computer Society Press, pp. 24-30.
7. Danyluk, A.P. and F.J. Provost (1993) Small disjuncts in action: Learning to diagnose errors in the local loop of the telephone network, in: Proceedings of the Tenth International Conference on Machine Learning, Morgan kaufmann, Los Altos, CA.
8. Gomez, J., Y. Lee, and D.R. Mattison (1993). Identification of developmental toxicants using a rule learning expert system, in: Program and Abstracts: The Fourteenth Annual Meetings of the American College of Toxicology.
9. Gomez, J., Y. Lee and D.R. Mattison (1994) RL: An innovative tool for predicting developmental toxicity, in: Program and Abstracts: The 33rd Annual Meeting of the Society of Toxicology.
10. Haseman, J.K. and A.-M. Lockhart (1993) Correlations between chemically related site-specific carcinogenic effects in long-term studies in rats and mice. Environ. Health Perspect., 101, 50-54.
11. Hennessy, D., V. Gopalakrishnan, B.G. Buchanan, J.M. Rosenberg and D. Subramanian (1994) Induction of rules for biological macromolecule crystallization, in: Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, AAAI Press, pp. 179-187.
12. Hoel, D.G., J.K. Haseman, M.D. Hogan, J. Huff and E.E. McConnell (1988) The impact of toxicity on carcinogenicity studies: implications for risk assessment. Carcinogenesis, 9, 2045-2052.
13. Huff, J. (1993) Absence of morphologic correlation between chemical toxicity and chemical carcinogenesis. Environ. Health Perspect., 101, 45-54.
14. Klopman, G. and H.S. Rosenkranz (1991) Quantification of the predictivity of some short-term assays for carcinogenicity in rodents. Mutation Res., 253, 237-240.
15. Krenzelok, E.P., F.J. Provost, T.D. Jacobsen, J.M. Aronis and B.G. Buchanan (1995). Assessing patient referral patterns to a health care facility in plant exposure patients using computer artificial intelligence, in: European Association of Poisons Centers and Clinical Toxicologists Scientific Meeting.
16. Lee, Y. and S.H. Clearwater (1992) Tools for automating experiment design: A machine learning approach, in: Proceedings of the Fourth International Conference on Tools with Artificial Intelligence, IEEE Computer Society Press.
17. Lee, Y., B.G. Buchanan, D.R. Mattison, G. Klopman and H.S., Rosenkranz (1995) Learning rules to predict rodent carcinogenicity of non-genotoxic chemicals. Mutation Res., 328, 127-149.
18. Quinlan, J.R. (1993) C4.5: Prograls for machine learning. Morgan Kaufmann.
19. Tennant, R.W., M.R. Elwell, J.W. Spalding and R.A. Griesemer (1991) Evidence that toxic injury is not always associated with induction of chemical carcinogenesis. Mol. Carcinogen., 4, 420-440.