in silico toxicology

[ 1 ]: A. Maunz and C. Helma. Prediction of toxic effects of pharmaceutical agents. In K. V. Balakin, editor, Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery , New York, 2009. J. Wiley & Sons, Inc. [ .pdf ]
[ 2 ]: A. Maunz, C. Helma, and S. Kramer. Large-scale graph mining using backbone refinement classes. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-09) , page in press, 2009. [ .pdf ]
[ 3 ]: F. Hammann, H. Gutmann, U. Jecklin, A. Maunz, C. Helma, and J. Drewe. Development of decision tree models for substrates, inhibitors and inducers of P-glycoprotein. Current Drug Metabolism , 10:339-46, 2009.
[ 4 ]: Felix Hammann, Heike Gutmann, Ulli Baumann, Christoph Helma, and Juergen Drewe. Classification of cytochrome p(450) activities using machine learning methods. Molecular pharmaceutics , 6:1920-6, 2009.
[ 5 ]: A. Maunz and C. Helma. Prediction of chemical toxicity with local support vector regression and activity-specific kernels. SAR QSAR Environ. Res. , 19:413-431, 2008. [ .pdf ]
[ 6 ]: R. Benigni, T. I. Netzeva, E. Benfenati, C. Bossa, R. Franke, C. Helma, E. Hulzebos, C. Marchant, A. Richard, Y.-T. Woo, and C. Yang. The expanding role of predictive toxicology: an update on the (Q)SAR models for mutagens and carcinogens. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. , 25:53-97, 2007.
[ 7 ]: C. Helma. Lazy structure-activity relationships ( lazar ) for the prediction of rodent carcinogenicity and Salmonella mutagenicity. Molecular Diversity , 10:147-158, 2006. [ .pdf ]
[ 8 ]: C. Helma and J. Kazius. Artificial intelligence and data mining for toxicity prediction. Current Computer-Aided Drug Design , 2:1-19, 2006. [ .pdf ]
[ 9 ]: M. Vracko, V. Bandelj, P. Barbieri, E. Benfenati, Q. Chaudhry, M. Cronin, J. Devillers, A. Gallegos, G. Gini, P. Gramatica, C. Helma, D. Neagu, T. Netzeva, M. Pavan, G. Patlevicz, M. Randic, I. Tsakovska, and A. Worth. Validation of counter propagation neural network models for predictive toxicology according to the OECD principles. A case study. SAR QSAR Environ. Res. , 17:265-84, 2006.
[ 10 ]: C. Helma. Predictive Toxicology . CRC Press, Boca Raton, 2005.
[ 11 ]: C. Helma. lazar: Lazy Structure - Activity Relationships for toxicity prediction. In C. Helma, editor, Predictive Toxicology , pages 479-499. CRC Press, Boca Raton, 2005.
[ 12 ]: C. Helma. In Silico predictive toxicology: The state-of-the-art and strategies to predict human health effects. Current Opinions in Drug Discovery & Development , 8:27-31, 2005. [ .pdf ]
[ 13 ]: C. Helma. A brief introduction to predictive toxicology. In C. Helma, editor, Predictive Toxicology . CRC Press, Boca Raton, 2005.
[ 14 ]: S. Kramer and C. Helma. Machine learning and data mining. In C. Helma, editor, Predictive Toxicology , pages 223-254. CRC Press, Boca Raton, 2005.
[ 15 ]: C. Helma, T. Kramer, S. Kramer, and L. DeRaedt. Data Mining and Machine Learning techniques for the identification of mutagenicity inducing substructures and Structure-Activity Relationships of noncongeneric compounds. J. Chem. Inf. Comput. Sci. , 44:1402-1411, 2004. [ http ]
[ 16 ]: C. Helma. Data mining and knowledge discovery in predictive toxicology. SAR QSAR Environ. Res. , 15:367-383, 2004.
[ 17 ]: C. Helma and S. Kramer. A survey of the Predictive Toxicology Challenge. Bioinformatics , 19:1179-1182, 2003. [ http ]
[ 18 ]: C. Helma, S. Kramer, and L. DeRaedt. The molecular feature miner MolFea. In M. Hicks and C. Kettner, editors, Proceedings of the Beilstein Workshop 2002: Molecular Informatics: Confronting Complexity , pages 79-93. Beilstein Institut, Frankfurt, 2003.
[ 19 ]: H. Toivonen, A. Srinivasan, R. D. King, S. Kramer, and C. Helma. Statistical evaluation of the Predictive Toxicology Challenge 2000-2001. Bioinformatics , 19:1183-1193, 2003. [ http ]
[ 20 ]: C. Helma. Data mining in toxicology. In J.P.V. Heuvel, W.F. Greenlee, G.H. Perdew, and W.B. Mattes, editors, Comprehensive Toxicology Vol XX. Cellular and Molecular Toxicology , pages 611-624. Elsevier, 2002.
[ 21 ]: F. Kassie, S. Rabot, M. Uhl, W. Huber, H.M. Qin, C. Helma, R. Schulte-Hermann, and S. Knasmüller. Chemoprotective effects of garden cress (lepidium sativum) and its constituents towards 2-amino-3-methyl-imidazo[4,5-f]quinoline (IQ)-induced genotoxic effects and colonicneoplastic lesions. Carcinogenesis , 23:1155-1161, 2002.
[ 22 ]: S. Kramer, E. Frank, and C. Helma. Fragment generation and Support Vector Machines for inducing SARs. SAR and QSAR in Environmental Research , 13:509-523, 2002.
[ 23 ]: E. Gottmann, S. Kramer, B. Pfahringer, and C. Helma. Data quality in predictive toxicology: Reproducibility of rodent carcinogenicity experiments. Environ. Health Perspect. , 109:509-514, 2001. [ .html ]
[ 24 ]: C. Helma, R.D. King, S. Kramer, and A. Srinivasan. The Predictive Toxicology Challenge 2000-2001. Bioinformatics , 17:107-108, 2001. [ .pdf ]
[ 25 ]: S. Kramer, L. De Raedt, and C. Helma. Molecular feature mining in HIV data. In Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-01) , pages 136-143, 2001.
[ 26 ]: C. Helma, S. Kramer, B. Pfahringer, and E. Gottmann. Data quality in predictive toxicology: Identification of chemical structures and calculation of chemical properties. Environ. Health Perspect. , 108:1029-1033, 2000. [ .html ]
[ 27 ]: C. Helma, E. Gottmann, and S. Kramer. Knowledge discovery and data mining in toxicology. Stat Methods Med Res. , 9:329-358, 2000. [ .pdf ]
[ 28 ]: C. Helma, S. Kramer, and B. Pfahringer. Carcinogenicity prediction for noncongeneric compounds: Experiments with the Machine Learning Program SRT and various sets of chemical descriptors. In Molecular Modelling and Prediction of Bioactivity , page 464, 2000.
[ 29 ]: C. Helma and M. Uhl. A public domain image analysis program for the single cell gel electrophoresis (comet) assay. Mutation Res. , 466:9-15, 2000. [ .pdf ]
[ 30 ]: C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer. The application of machine learning algorithms to detect chemical properties responsible for carcinogenicity. In K. Gundertofte and F.S. Jorgensen, editors, Molecular Modeling and Prediction of Bioactivity , pages 464-466, New York, 2000. Kluwer Academic/Plenum Publishers.
[ 31 ]: C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer. Artificial Intelligence Methoden zur Vorhersage der Kanzerogenität organischer Verbindungen. In H. Schöffl, H. Spielmann, and H.A. Tritthart, editors, Ersatz- und Ergänzungsmethoden zu Tierversuchen: Forschung ohne Tierversuche , pages 128-134, Wien-New York, 2000. Springer Verlag.
[ 32 ]: M. Uhl, C. Helma, and S. Knasmüller. Evaluation of the single cell gel electrophoretic assay with human hepatoma (HepG2) cells. Mutation Res. , 468:213-225, 2000.
[ 33 ]: C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer. Data quality issues in toxicological knowledge discovery. In Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools , pages 8-11, Menlo Park, California, 1999. AAAI Press.
[ 34 ]: B. Pfahringer, E. Gottmann, C. Helma, and S. Kramer. Efficiency/representational issues in toxicological knowledge discovery. In Predictive Toxicology of Chemicals: Experiences and Impact of AI Tools , pages 86-89, Menlo Park, California, 1999. AAAI Press.
[ 35 ]: M. Uhl, C. Helma, and S. Knasmüller. Single-cell gel electrophoresis assays with human-derived hepatoma (HepG2) cells. Mutation Res. , 441:215-224, 1999.
[ 36 ]: C. Helma, E. Gottmann, S. Kramer, and B. Pfahringer. The application of machine learning algorithms to detect chemical properties responsible for carcinogenicity. In Molecular Modelling and Prediction of Bioactivity. Proceedings of the 12th European Symposium on Quantitative Structure-Activity Relationships , 1998.
[ 37 ]: C. Helma, P. Eckl, E. Gottmann, F. Kassie, W. Rodinger, H. Steinkellner, C. Windpassinger, R. Schulte-Hermann, and S. Knasmüller. Genotoxic and ecotoxic effects of groundwaters and their relation to routinely measured chemical parameters. Environ. Sci. Technol. , 32:1799-1805, 1998.
[ 38 ]: S. Knasmüller, C. Helma, P. Eckl, E. Gottmann, H. Steinkellner, F. Kassie, T. Haider, W. Parzefall, and R. Schulte-Hermann. Investigations on genotoxic effects of groundwater from the Mitterndorfer Senke from the vicinity of Wiener Neustadt. Wiener Klinische Wochenschrift , 110:824-833, 1998.
[ 39 ]: S. Kramer, B. Pfahringer, and C. Helma. Stochastic propositionalization of non-determinate background knowledge. In Proceedings of the 8th International Workshop on Inductive Logic Programming (ILP-98) , pages 80-94, Berlin Heidelberg New York, 1998. Springer.
[ 40 ]: H. Steinkellner, M.S. Kong, C. Helma, S. Ecker, T.H. Ma, O. Horak, M. Kundi, and S. Knasmüller. Genotoxic effects of heavy metals: Comparative investigation with plant bioassays. Environ. Mol. Mutagen. , 31:183-191, 1998.
[ 41 ]: C. Helma and S. Knasmüller. Die Belastung von Gewässern mit gentoxischen Substanzen IIa: Die Quellen gentoxischer Kontaminationen (Industrielle Emissionen). UWSF-Z.Umweltchem.Ökotox. , 9:41-48, 1997.
[ 42 ]: C. Helma and S. Knasmüller. Die Belastung von Gewässern mit gentoxischen Substanzen IIb: Die Quellen gentoxischer Kontaminationen (Nichtindustrielle Emissionen). UWSF-Z.Umweltchem.Ökotox. , 9:163-168, 1997.
[ 43 ]: C. Helma. Die Situation der Chlorchemie in Östereich: Chlorhältige Pflanzenschutz- Holzschutz und Wasserdesinfektionsmittel - Entwicklungen im Zeitraum 1993 bis 1997. Technical report, Gesellschaft Österreichischer Chemiker, 1997.
[ 44 ]: S. Knasmüller, W. Parzefall, C. Helma, F. Kassie, S. Ecker, and R. Schulte-Hermann. Toxic effects of griseofulvin: Disease models, mechanisms, and risk assessment. Critical Reviews in Toxicology , 27:495-537, 1997.
[ 45 ]: S. Kramer, B. Pfahringer, and C. Helma. Mining for causes of cancer: Machine learning experiments at various levels of detail. In Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97) , Menlo Park, CA, 1997. AAAI Press.
[ 46 ]: C. Helma, V. Mersch-Sundermann, V.S. Houk, U. Glasbrenner, C. Klein, L. Wenquing, K. Fekadu, R. Schulte-Hermann, and S. Knasmüller. Comparative evaluation of four bacterial assays for the detection of genotoxic effects in water samples. Environ. Sci. Technol. , 30:897-907, 1996.
[ 47 ]: C. Helma, L. Kronberg, T.H. Ma, and S. Knasmüller. Genotoxic effects of the chlorinated hydroxyfuranones 3-chloro-4-(dichloromethyl)-5-hydroxy-2[5H]-furanone and 3,4-dichloro-5-hydroxy-2[5H]-furanone in Tradescantia micronucleus assays. Mutation Res. , 346:181-186, 1995.
[ 48 ]: C. Helma. Erfahrungen mit dem Einsatz biologischer Mutationstests zur Verfahrensoptimierung und Umweltkontrolle. In Handbuch der Umwelttechnik 1995 , pages 266-267. Wien, 1995.
[ 49 ]: C. Helma. Detection of genotoxic contaminations in water. In M. Guminska and J. Miedzobrodzki, editors, Molecular Biology for Environment and Man , pages 99-111. 1995.
[ 50 ]: C. Helma, R. Sommer, R. Schulte-Hermann, and S. Knasmüller. Enhanced clastogenicity of contaminated ground water following UV irradiation detected by the Tradescantia micronucleus assay. Mutation Res. , 323:93-98, 1994.
[ 51 ]: C. Helma, S. Knasmüller, and R. Schulte-Hermann. Die Belastung von Wässern mit gentoxischen Substanzen I. Methoden zur Prüfung der Gentoxizität. UWSF-Z.Umweltchem.Ökotox. , 6:277-288, 1994.
[ 52 ]: C. Helma, S. Knasmüller, and R. Schulte-Hermann. Biologische Tests zur Prüfung der Gentoxizität: Einsatzmöglichkeiten zur Verfahrensoptimierung und Emissionskontrolle. In Brandl et al., editor, Ecoinforma 94. Bd 9, Kanzerogenese durch Umweltchemikalien , pages 497-512. Wien, 1994.
[ 53 ]: E. Fassold, C. Helma, S. Knasmüller, and R. Sattelberger. Die Situation der Chlorchemie in Östereich, 8. Teil: Chlorhältige Pflanzenschutz- Holzschutz und Wasserdesinfektionsmittel. Technical report, Gesellschaft Österreichischer Chemiker, 1993.
[ 54 ]: C. Helma et.al. Abfallarme Großküche. Technical report, Österreichisches Ökologie Institut, 1992.
[ 55 ]: C. Helma et.al. Ausstieg aus der Müllverbrennung. Technical report, Österreichisches Ökologie Institut, 1991.