Molecular Networks GmbH Leading References (by Topics) Chemoinformatics Gasteiger, J.; Bauerschmidt, S.; Burkard, U.; Hemmer, M.C.; Herwig, A.; von Homeyer, A.; Höllering, R.; Kleinöder, T.; Kostka, T.; Schwab, C.; Selzer, P.; Steinhauer, L. Decision Support Systems for Chemical Structure Representation, Reaction Modeling, and Spectra Simulation. SAR & QSAR in Environm. Res. 2002, 13, 89-110. http://www.ingentaconnect.com/content/tandf/gsar/2002/00000013/00000001/art00007 Gasteiger, J.; Engel, T. (Editors) Chemoinformatics – A Textbook. Wiley-VCH, Weinheim, 2003, 650 pages (ISBN 3-527-30681-1) http://www2.chemie.uni-erlangen.de/publications/ci-book/textbook.html Gasteiger, J. (Editor) Handbook of Chemoinformatics – From Data to Knowledge. WileyVCH, Weinheim, 2003, 1850 pages (ISBN 3-527-30680-3) www2.chemie.uni-erlangen.de/publications/ci-book/handbook.html Drug Design & Property Prediction Structure Representation Sadowski, J.; Gasteiger, J. From Atoms and Bonds to Three-dimensional Atomic Coordinates: Automatic Model Builders. Chemical Reviews 1993, 93, 2567-2581. dx.doi.org/10.1021/cr00023a012 Gasteiger, J. Physicochemical Effects in the Representation of Molecular Structures for Drug Designing. Mini Rev. Med. Chem. 2003, 3, 789-796. www.ingentaconnect.com/content/ben/mrmc/2003/00000003/00000008/art00002 Aires-de-Sousa, J.; Gasteiger, J.; Gutman, I.; Vidovic, D. Chirality Codes and Molecular Structure. J. Chem. Inf. Comput. Sci. 2004, 44, 831-836. http://dx.doi.org/10.1021/ci030410h Renner, S.; Schwab, C.H.; Schneider, G.; Gasteiger, J. Impact of conformational flexibility on three-dimensional similarity searching using correlation vectors. J. Comp. Inf. Model. 2006, 46, 2324-2332. dx.doi.org/10.1021/ci050075s Data Analysis & Property Prediction Zupan, J.; Gasteiger, J. Neural Networks in Chemistry and Drug Design. Second Edition, Wiley-VCH, Weinheim, 1999, 380 pages. http://www.wiley-vch.de/publish/dt/books/bySubjectCH00/bySubSubjectCH65/3-52729779-0/?sID=4fdfcba4d030cc72669dffd159153423 1 Molecular Networks GmbH Gasteiger, J.; Teckentrup, A.; Terfloth, L.; Spycher, S. Neural Networks as Data Mining Tools in Drug Design. J. Phys. Org. Chem. 2003, 16, 232-245. dx.doi.org/10.1002/poc.597 Yan, A.; Gasteiger, J. Prediction of Aqueous Solubility of Organic Compounds by Topological Descriptors. QSAR Comb. Sci. 2003, 22, 821-829. dx.doi.org/10.1002/qsar.200330822 Teckentrup, A.; Briem, H.; Gasteiger, J. Mining High-Throughput Screening Data of Combinatorial Libraries: Development of a Filter to Distinguish Hits from Nonhits. J. Chem. Inf. Comput. Sci.2004, 44, 626-634. dx.doi.org/10.1021/ci034223v Spycher, S.; Pellegrini, E.; Gasteiger, J. Use of Structure Descriptors To Discriminate between Modes of Toxic Action of Phenols. J. Chem. Inf. Model. 2005, 45, 200-208. dx.doi.org/10.1021/ci0497915 Reaction Simulation & Synthesis Design Knowledge from Reaction Databases Parlow, A.; Weiske, C.; Gasteiger, J. ChemInform - An Integrated Information System on Chemical Reactions. J. Chem. Inf. Comput. Sci. 1990, 30, 400-402. http://dx.doi.org/10.1021/ci00068a009 Chen, L.; Gasteiger, J. Knowledge Discovery in Reaction Databases: Landscaping Organic Reactions by a Self-Organizing Neural Network. J. Am. Chem. Soc. 1997, 119, 4033-4042. http://dx.doi.org/10.1021/ja960027b Reitz, M.; Sacher, O.; Tarkhov, A.; Trümbach, D.; Gasteiger, J. Enabling the exploration of biochemical pathways. Org. Biomol. Chem. 2004, 2, 3226-3237. dx.doi.org/10.1039/B410949J Reaction Prediction Höllering, R.; Gasteiger, J.; Steinhauer, L.; Schulz, K.-P.; Herwig, A. The Simulation of Organic Reactions: From the Degradation of Chemicals to Combinatorial Synthesis. J. Chem. Inf. Comput. Sci. 2000, 40, 482-494. http://dx.doi.org/10.1021/ci990433p Kostka, T.; Selzer, P.; Gasteiger, J. A Combined Application of Reaction Prediction and Infrared Spectra Simulation for the Identification of Degradation Products of s-Triazine Herbicides. Chemistry Eur. J. 2001, 7, 2254-2260. http://dx.doi.org/10.1002/1521-3765(20010518)7:10%3C2254::AIDCHEM2254%3E3.0.CO;2-# Boda, K.; Seidel, T.; Gasteiger, J. Structure and reaction based evaluation of synthetic accessibility. J. Comp.-Aided. Mol. Des. 2007, 21, 311-325. DOI 10.1007/s10822-006-9099-2 2 Molecular Networks GmbH Synthesis Design Ihlenfeldt, W.-D.; Gasteiger, J. Computer-Assisted Planning of Organic Syntheses: The Second Generation of Programs. Angew. Chem. Int. Ed. Engl., 1995, 34, 2613-2633. dx.doi.org/10.1002/anie.199526131 Pförtner, M.; Sitzmann, M. In Handbook of Chemoinformatics – From Data to Knowledge; Gasteiger, J; Engel, T., Eds.; Wiley-VCH, Weinheim, 2003, 1457-1507. www2.chemie.uni-erlangen.de/publications/ci-book/handbook.html Spectra Simulation Selzer, P.; Gasteiger, J.; Thomas, H.; Salzer, R. Rapid Access to Infrared Reference Spectra of Arbitrary Organic Compounds: Scope and Limitations of an Approach to the Simulation of Infrared Spectra by Neural Networks. Chem. Eur. J. 2000, 6, 920-927. dx.doi.org/10.1002/(SICI)1521-3765(20000303)6:5<920::AID-CHEM920>3.0.CO;2-W Hemmer, M.C.; Gasteiger, J. Prediction of Three-Dimensional Molecular Structures Using Information from Infrared Spectra. Anal. Chim. Acta 2000, 420, 145-154. dx.doi.org/10.1016/S0003-2670(00)00876-X Aires de Sousa, J. Hemmer, M.C.; Gasteiger, J. Prediction of 1H NMR Chemical Shifts Using Neural Networks. Anal. Chem. 2002, 74, 80-90. dx.doi.org/10.1021/ac010737m Da Costa, F. B.; Binev, Y.; Gasteiger, J.; Aires-de-Sousa, J. Structure-based predictions of 1 H NMR chemical shifts of sesquiterpene lactones using neural networks. Tetrahedron Letters 2004, 45, 6931-6935. dx.doi.org/10.1016/j.tetlet.2004.07.082 Prediction of Metabolism Endogenous Metabolism Reitz, M.; Sacher, O.; Tarkhov, A.; Trümbach, D.; Gasteiger, J. Enabling the exploration of biochemical pathways. Org. Biomol. Chem. 2004, 2, 3226-3237. dx.doi.org/10.1039/B410949J Reitz, M.; von Homeyer, A.; Gasteiger, J. Query Generation to Search for Inhibitors of Enzymatic Reactions. J. Chem. Inf. Model. 2006, 46, 2333-2341. dx.doi.org/10.1021/ci050503u Metabolism of Xenobiotics Terfloth, L.; Bienfait, B.; Gasteiger, J. Ligand-Based for the Isoform Specificity of Cytochrome P450 3A4, 2D6, and 2C9 Substrates. J. Chem. Inf. Model. 2007, 47, 16881701. DOI 10.1021/ci700010t 3 Molecular Networks GmbH References by Products ADRIANA.Code Overview of applications of structure descriptors Gasteiger, J. Physicochemical Effects in the Representation of Molecular Structures for Drug Designing. Mini Rev. Med. Chem. 2003, 3, 789-796. www.ingentaconnect.com/content/ben/mrmc/2003/00000003/00000008/art00002 Gasteiger, J. A Hierarchy of Structure Representations. In Handbook of Chemoinformatics, J. Gasteiger, Editor, Wiley-VCH, Weinheim, 2003, 1034-1061. www2.chemie.uni-erlangen.de/publications/ci-book/handbook.html Clustering of compounds according to their biological activity Bauknecht, H.; Zell, A.; Bayer, H.; Levi, P.; Wagener, M.; Sadowski, J.; Gasteiger, J. Locating Biologically Active Compounds in Medium-Sized Heterogeneous Datasets by Topological Autocorrelation Vectors: Dopamine and Benzodiazepine Agonists. J. Chem. Inf. Comput. Sci.1996, 36, 1205-1213. dx.doi.org/10.1021/ci960346m Wagener, M.; Sadowski, J.; Gasteiger, J. Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks. J. Am. Chem. Soc. 1995, 117, 7769-7775. dx.doi.org/10.1021/ja00134a023 Quantitative prediction of biological activities Wagener, M.; Sadowski, J.; Gasteiger, J. Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks. J. Am. Chem. Soc. 1995, 117, 7769-7775. dx.doi.org/10.1021/ja00134a023 Moro, S.; Bacilieri, M.; Ferrari, C.; Spalluto, G. Autocorrelation of Molecular Electrostatic Surface Properties Combined with Partial Least Squares Analysis as Alternative Attractive Tool to Generate Ligand-Based 3D-QSARs. Current Drug Discovery Technologies 2005, 2, 13-21. www.ingentaconnect.com/content/ben/cddt/2005/00000002/00000001/art00002 Moro, S.; Bacilieri, M.; Cacciari, B.; Spalluto, G. Autocorrelation of Molecular Electrostatic Surface Properties Combined with Partial Least Squares Analysis as as New Strategy for the Prediction of Activity of Human A3 Adenosine Receptor Antagonists. J. Med. Chem. 2005, 48, 5698-5704. dx.doi.org/10.1021/jm0502440 4 Molecular Networks GmbH Moro, S.; Bacilieri, M.; Cacciari, B.; Bolcato, C.; Cusan, C.; Pastorin, G.; Klotz, K.-N.; Spalluto, G. The application of a 3D-QSAR (autoMEP/PLS) approach as an efficient pharmacodynamic-driven filtering method for small-sized virtual libraries: Application to a lead optimization of a human A3 adenosine receptor antagonist. Bioorg. Med. Chem. 2006, 14, 4923-4932. dx.doi.org/10.1016/j.bmc.2006.03.010 Comparison of libraries of compounds Bauknecht, H.; Zell, A.; Bayer, H.; Levi, P.; Wagener, M.; Sadowski, J.; Gasteiger, J. Locating Biologically Active Compounds in Medium-Sized Heterogeneous Datasets by Topological Autocorrelation Vectors: Dopamine and Benzodiazepine Agonists. J. Chem. Inf. Comput. Sci. 1996, 36, 1205-1213. dx.doi.org/10.1021/ci960346m Wagener, M.; Sadowski, J.; Gasteiger, J. Assessing Similarity and Diversity of Combinatorial Libraries by Spatial Autocorrelation Functions and Neural Networks. Angew. Chem. Int. Ed. Engl. 1996, 34, 2674-2677. dx.doi.org/10.1002/anie.199526741 Analysis of results of high-throughput screening Teckentrup, A.; Briem, H.; Gasteiger, J. Mining High-Throughput Screening Data of Combinatorial Libraries: Development of a Filter to Distinguish Hits from Nonhits. J. Chem. Inf. Comput. Sci.2004, 44, 626-634. dx.doi.org/10.1021/ci034223v Analysis of the spatial and electronic requirements for biological activity Holzgrabe, U.; Wagener, M.; Gasteiger, J. Comparison of Structurally Different Allosteric Modulators of Muscarinic Receptors by Self-organizing Neural Networks. J. Mol. Graphics 1996, 14, 185-193. dx.doi.org/10.1016/S0263-7855(96)00060-4 Anzali, S.; Barnickel, G.; Krug, M.; Sadowski, J.; Wagener, M.; Gasteiger, J.; Polanski, J. The Comparison of Geometric and Electronic Properties of Molecular Surfaces by Neural Networks: Application to the Analysis of Corticosteroid Binding Globulin Activity of Steroids. J. Comput.-Aided Mol. Design 1996, 10, 521-534. dx.doi.org/10.1007/BF00134176 Polanski, J.; Ratajczak, A.; Gasteiger, J.; Galdecki, Z.; Galdecka, E. Molecular Modeling and X-Ray Analysis for a Structure-Taste Study of α-Arylsulfonylalkanoic Acids. J. Mol. Struct. 1997, 407, 71-80. dx.doi.org/10.1016/S0022-2860(96)09703-7 Polanski, J.; Gasteiger, J.; Wagener, M.; Sadowski, J. The Comparison of Molecular Surfaces by Neural Networks and Its Application to Quantitative Structure Activity Studies. Quant. Struct.-Act. Relat. 1998, 17, 27-36. dx.doi.org/10.1002/(SICI)1521-3838(199801)17:01<27::AID-QSAR27>3.0.CO;2-A 5 Molecular Networks GmbH Handschuh, S.; Chen, J.; Goldfuss, B.; Houk, K.N.; Gasteiger, J. Steroid Binding by Antibodies and Artificial Receptors: Exploration of Theoretical Methods to Determine the Origins of Binding Affinities and Specificities. J. Comput.-Aided Mol. Design 2000, 14, 611-629. dx.doi.org/10.1023/A:1008188322239 Polanski, J.; Zouhiri, F.; Jeanson, L.; Desmaële, D.; d'Angelo, J.; Mouscadet, J.-F.; Gieleciak, R.; Gasteiger, J.; LeBret, M. Use of Kohonen Neural Network for Rapid Screening of Ex Vivo Anti-HIV Activity of Styrylquinolines. J. Med. Chem. 2002, 45, 4647-4654. dx.doi.org/10.1021/jm020845g Wagner, S.; Hofmann, A.; Siedle, B.; Terfloth, L.; Merfort, I.; Gasteiger, J. Development of a Structural Model for NF-kB Inhibition of Sesquiterpene Lactones Using SelfOrganizing Neural Networks. J. Med. Chem. 2006, 49, 2241-2252. dx.doi.org/10.1021/jm051125n Finding new lead structures and lead hopping Bauknecht, H.; Zell, A.; Bayer, H.; Levi, P.; Wagener, M.; Sadowski, J.; Gasteiger, J. Locating Biologically Active Compounds in Medium-Sized Heterogeneous Datasets by Topological Autocorrelation Vectors: Dopamine and Benzodiazepine Agonists. J. Chem. Inf. Comput. Sci. 1996, 36, 1205-1213. dx.doi.org/10.1021/ci960346m Terfloth, L.; Gasteiger, J. Electronic Screening: Lead Finding from Database Mining. In The Practice of Medicinal Chemistry. 2nd Edition, Wermuth, C.G., Ed., Elsevier, Amsterdam, NL, 2003, pp. 131-145. books.elsevier.com/uk/chemistry/uk/subindex.asp?maintarget=&isbn=0127444815 Prediction of aqueous solubility of organic compounds Yan, A.; Gasteiger, J. Prediction of Aqueous Solubility of Organic Compounds Based on a 3D Structure Representation. J. Chem. Inf. Comput. Sci. 2003, 43, 429-434. dx.doi.org/10.1021/ci025590u Yan, A.; Gasteiger, J. Prediction of Aqueous Solubility of Organic Compounds by Topological Descriptors. QSAR Comb. Sci. 2003, 22, 821-829. dx.doi.org/10.1002/qsar.200330822 Yan, A.; Gasteiger, J.; Krug, M.; Anzali, S. Linear and Nonlinear Functions on Modeling the Aqueous Solubility of Organic Compounds by Two Structure Representation Methods. J. Comput.-Aided Mol. Design 2004, 18, 75-87. dx.doi.org/10.1023/B:jcam.0000030031.81235.05 6 Molecular Networks GmbH Discrimination between different toxic modes of action Spycher, S.; Pellegrini, E.; Gasteiger, J. Use of Structure Descriptors To Discriminate between Modes of Toxic Action of Phenols. J. Chem. Inf. Model. 2005, 45, 200-208. dx.doi.org/10.1021/ci0497915 Dye design Greaves, A.J.; Gasteiger, J. The Use of Self-Organising Neural Networks in Dye Design. Dyes and Pigments 2001, 49, 51-63. dx.doi.org/10.1016/S0143-7208(00)00110-8 BioPath & BioPath.Explore Reitz, M.; Sacher, O.; Tarkhov, A.; Trümbach, D.; Gasteiger, J. Enabling the exploration of biochemical pathways. Org. Biomol. Chem. 2004, 2, 3226-3237. dx.doi.org/10.1039/B410949J Gasteiger, J.; Reitz, M.; Han, Y,; Sacher, O. Analyzing Biochemical Pathways Using Neural Networks and Genetic Algorithms. Aust. J. Chem. 2006, 59, 854-858. dx.doi.org/10.1071/CH06140 Reitz, M.; von Homeyer, A.; Gasteiger, J. Query Generation to Search for Inhibitors of Enzymatic Reactions. J. Chem. Inf. Model. 2006, 46, 2333-2341. dx.doi.org/10.1021/ci050503u Kastenmueller, G.; Gasteiger, J.; Mewes, H.-W. An environmental perspective on largescale genome clustering based on metabolic capabilities. Bioinformatics 2008, 24, 56-62. Sacher, O.; Reitz, M.; Gasteiger, J. Investigations of Enzyme-Catalyzed Reactions Based on Physicochemical Descriptors Applied to Hydrolases. J. Chem. Inf. Model. 2009, 49, 1525-1534. http://dx.doi.org/10.1021/ci800277f Kastenmüller, G.; Schenk, M.E.; Gasteiger, J.; Mewes, H.-W. Uncovering metabolic pathways relevant to phenotypic traits of microbial genomes. Genome Biol., 2009, 10:R28. http://dx.doi.org/10.1186/gb-2009-10-3-r28 CORINA Hiller, C.; Gasteiger, J. Ein automatisierter Molekülbaukasten. In Software-Entwicklung in der Chemie, Vol 1; Gasteiger, J., Ed.; Springer: Berlin, 1987; pp 53-66. scholle.oc.uni-kiel.de/users/cic/tagungen/index.html Gasteiger, J.; Rudolph, C.; Sadowski, J. Automatic Generation of 3D Atomic Coordinates for Organic Molecules. Tetrahedron Comp. Method.1990, 3, 537-547. dx.doi.org/10.1016/0898-5529(90)90156-3 7 Molecular Networks GmbH Sadowski, J.; Rudolph, C.; Gasteiger, J. The Generation of 3D Models of Host-guest Complexes. Anal. Chim. Acta 1992, 265, 233-241. dx.doi.org/10.1016/0003-2670(92)85029-6 Sadowski, J.; Gasteiger, J. Polygon Patterns for the Generation of Conformations of Large Rings. In Software Development in Chemistry, Vol 7; Ziessow, D., Ed.; Gesellschaft Deutscher Chemiker: Frankfurt am Main, 1993; pp 65-76. scholle.oc.uni-kiel.de/users/cic/tagungen/index.html Sadowski, J.; Gasteiger, J. From Atoms and Bonds to Three-dimensional Atomic Coordinates: Automatic Model Builders. Chemical Reviews 1993, 93, 2567-2581. dx.doi.org/10.1021/cr00023a012 Sadowski, J.; Gasteiger, J.; Klebe, G. Comparison of Automatic Three-Dimensional Model Builders Using 639 X-Ray Structures. J. Chem. Inf. Comput. Sci. 1994, 34, 1000-1008. dx.doi.org/10.1021/ci00020a039 Sadowski, J., Three-Dimensional Structure Generation: Automation. In Encyclopedia of Computational Chemistry, Schleyer, P.v.R.; Allinger, N.L.; Clark, T.; Gasteiger, J.; Kollman, P.A.; Schaefer, III, H.F.; Schreiner, P.R. (Eds.), John Wiley & Sons, Inc., Chichester, UK, 1998; pp.2976-2988. www.wiley-vch.de/publish/dt/books/ISBN0-471-96588-X Schönberger, H.; Schwab, C.H.; Hirsch, A; J. Gasteiger, J. Molecular Modelling of Fullerene Dendrimers. J. Mol. Model. 2000, 6, 379-395. dx.doi.org/10.1007/s0089400060379 Sadowski, J. 3D Structure Generation. In Handbook of Chemoinformatics - From Data to Knowledge. J. Gasteiger, J.; Engel, T., Eds., Wiley-VCH, Weinheim, 2003, pp. 231-261. www2.chemie.uni-erlangen.de/publications/ci-book/handbook.html Sadowski, J.; Schwab, C.H.; 3D Structure Generation and Conformational Searching. In Computational Medicinal Chemistry and Drug Discovery, Bultinck, P.; De Winter, H.; Langenaeker, W.; Tollenaere J.P., Eds., Dekker Inc., New York, 2004; pp. 151-212. books.google.de/books?vid=ISBN0824747747&id=_sWxoVrxY9sC&printsec=toc&... isoCYP Terfloth, L.; Bienfait, B.; Gasteiger, J. Ligand-Based for the Isoform Specificity of Cytochrome P450 3A4, 2D6, and 2C9 Substrates. J. Chem. Inf. Model. 2007, 47, 16881701. http://dx.doi.org/10.1021/ci700010t Michielan, L.; Terfloth, L.; Gasteiger, J.; Moro, S. Comparison of Multilabel and SingleLabel Classification Applied to the Prediction of the Isoform Specificity of Cytochrome P450 Substrates. J. Chem. Inf. Model. 2009, 49, 2588-2605. http://dx.doi.org/10.1021/ci900299a 8 Molecular Networks GmbH ROTATE Schwab, C.H. Conformational Analysis and Searching. In Handbook of Chemoinformatics – From Data ot Knowledge; Gasteiger, J; Engel Th., Eds.; Wiley-VCH, Weinheim, 2003, 262-301. www2.chemie.uni-erlangen.de/publications/ci-book/handbook.html Sadowski, J.; Schwab, C.H.; Gasteiger, J. 3D Structure Generation and Conformational Searching. In Computational Medicinal Chemistry and Drug Discovery; Bultinck, P.; De Winter, H.; Langenaeker, W.; Tollenaere J.P., Eds., Dekker Inc., New York, 2004, 151212. books.google.de/books?vid=ISBN0824747747&id=_sWxoVrxY9sC&printsec=toc&... Renner, S.; Schwab, C.H.; Schneider, G.; Gasteiger, J. Impact of conformational flexibility on three-dimensional similarity searching using correlation vectors. J. Comp. Inf. Model. 2006, 46, 2324-2332. dx.doi.org/10.1021/ci050075s SONNIA Books on neural networks in chemistry Zupan, J.; Gasteiger, J. Neural Networks for Chemists: An Introduction. VCH-Verlag, Weinheim, 1993, 300 pages. Zupan, J.; Gasteiger, J. Neural Networks in Chemistry and Drug Design. Second Edition, Wiley-VCH, Weinheim, 1999, 380 pages. www.wiley-vch.de/publish/dt/books/bySubjectCH00/bySubSubjectCH65... Overviews on self-organizing neural networks in chemistry and drug design Zupan, J.; Gasteiger, J. Neuronale Netze in der Chemie. Angew. Chem. 1993, 105, 510536. dx.doi.org/10.1002/ange.19931050405 Zupan, J.; Gasteiger, J. Neural Networks in Chemistry. Angew. Chem. Int. Ed. Engl.1993, 32, 503-527. dx.doi.org/10.1002/anie.199305031 Anzali, S.; Gasteiger, J.; Holzgrabe, U.; Polanski, J.; Sadowski, J.; Teckentrup, A.; Wagener, M. The Use of Self-Organizing Neural Networks in Drug Design. In 3D QSAR in Drug Design - Volume 2; H. Kubinyi, G. Folkers, Y. C. Martin, Eds., Kluwer/ESCOM, Dordrecht, NL, 1998; pp. 273-299. www.springer.com/dal/home/generic/search/results?SGWID=1-40109-22-67588052-0 Terfloth, L.; Gasteiger, J. Self-organizing Neural Networks in Drug Design. Screening Trends in Drug Discovery 2001, 2(4), 49-51. www.gitverlag.com/wj/engine/de/pub/mag/screening 9 Molecular Networks GmbH Gasteiger, J.; Teckentrup, A.; Terfloth, L.; Spycher, S. Neural Networks as Data Mining Tools in Drug Design. J. Phys. Org. Chem. 2003, 16, 232-245. dx.doi.org/10.1002/poc.597 SYLVIA Boda, K.; Seidel, T.; Gasteiger, J. Structure and reaction based evaluation of synthetic accessibility. J. Comp.-Aided. Mol. Des. 2007, 21, 311-325. DOI 10.1007/s10822-006-9099-2 Zaliani, A.; Boda, K.; Seidel, T.; Herwig, A. Schwab, C.H.; Gasteiger, J.; Claußen, H.; Lemmen, C.; Degen, J.; Pärn, J.; Rarey, M. Second-generation de novo design: a view from a medicinal chemist perspective. J. Comp.-Aided. Mol. Des. 2009, 23, 593-602. http://dx.doi.org/10.1007/s10822-009-9291-2 THERESA & WODCA Ihlenfeldt, W.-D.; Gasteiger, J. Computer-Assisted Planning of Organic Syntheses: The Second Generation of Programs. Angew. Chem. Int. Ed. Engl., 1995, 34, 2613-2633. dx.doi.org/10.1002/anie.199526131 Pförtner, M.; Sitzmann, M. In Handbook of Chemoinformatics – From Data to Knowledge; Gasteiger, J; Engel Th., Eds.; Wiley-VCH, Weinheim, 2003, 1457-1507. www2.chemie.uni-erlangen.de/publications/ci-book/handbook.html Schwab, C.H.; Bienfait, B.; Gasteiger, J. Following the road step by step: A new reaction database-driven tool for stepwise retrosynthetic analysis. Oral presentation at the American Chemical Society 232nd National Meeting & Exposition, San Francisco, CA, USA, September 10-14, 2006. CINF 105, ACS 232nd National Meeting & Exposition, San Francisco, CA, USA Schwab, C.H.; Bienfait, B.; Gasteiger, J. Planning Organic Synthesis Using Reaction Types Derived from Reaction Databases. Oral presentation at the 8th International Conference on Chemical Structures, Noordwijkerhout, NL, June 1-5, 2008. http://www.int-conf-chem-structures.org/pdf/Presentations/D-2.pdf 10