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
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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
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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
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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
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Schwab, C.H.; Bienfait, B.; Gasteiger, J. Following the road step by step: A new reaction
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Oral presentation at the American Chemical Society 232nd National Meeting & Exposition,
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CINF 105, ACS 232nd National Meeting & Exposition, San Francisco, CA, USA
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Schwab, C.H.; Bienfait, B.; Gasteiger, J. Planning Organic Synthesis Using Reaction
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Oral presentation at the 8th International Conference on Chemical Structures,
Noordwijkerhout, NL, June 1-5, 2008.
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