| 2008 | ||
|---|---|---|
| 33 | Igor V. Tetko, Igor V. Rodchenkov, Mathias C. Walter, Thomas Rattei, Hans-Werner Mewes: Beyond the "best" match: machine learning annotation of protein sequences by integration of different sources of information. Bioinformatics 24(5): 621-628 (2008) | |
| 32 | Dimitrij Surmeli, Oliver Ratmann, Hans-Werner Mewes, Igor V. Tetko: FunCat functional inference with belief propagation and feature integration. Computational Biology and Chemistry 32(5): 375-377 (2008) | |
| 2006 | ||
| 31 | Igor V. Tetko, Vitaly P. Solov'ev, Alexey V. Antonov, Xiaojun Yao, Jean-Pierre Doucet, Bo Tao Fan, Frank Hoonakker, Denis Fourches, Piere Jost, Nicolas Lachiche, Alexandre Varnek: Benchmarking of Linear and Nonlinear Approaches for Quantitative Structure-Property Relationship Studies of Metal Complexation with Ionophores. Journal of Chemical Information and Modeling 46(2): 808-819 (2006) | |
| 30 | Andreas Ruepp, Octave Noubibou Doudieu, Jos van den Oever, Barbara Brauner, Irmtraud Dunger-Kaltenbach, Gisela Fobo, Goar Frishman, Corinna Montrone, Christine Skornia, Steffi Wanka, Thomas Rattei, Philipp Pagel, M. Louise Riley, Dmitrij Frishman, Dimitrij Surmeli, Igor V. Tetko, Matthias Oesterheld, Volker Stümpflen, Hans-Werner Mewes: The Mouse Functional Genome Database (MfunGD): functional annotation of proteins in the light of their cellular context. Nucleic Acids Research 34(Database-Issue): 568-571 (2006) | |
| 2005 | ||
| 29 | Alexey V. Antonov, Igor V. Tetko, Denis Kosykh, Dimitrij Surmeli, Hans-Werner Mewes: Exploiting scale-free information from expression data for cancer classification. German Conference on Bioinformatics 2005: 93-102 | |
| 28 | Igor V. Tetko, Axel Facius, Andreas Ruepp, Hans-Werner Mewes: Super paramagnetic clustering of protein sequences. BMC Bioinformatics 6: 82 (2005) | |
| 27 | Igor V. Tetko, Barbara Brauner, Irmtraud Dunger-Kaltenbach, Goar Frishman, Corinna Montrone, Gisela Fobo, Andreas Ruepp, Alexey V. Antonov, Dimitrij Surmeli, Hans-Werner Mewes: MIPS bacterial genomes functional annotation benchmark dataset. Bioinformatics 21(10): 2520-2521 (2005) | |
| 26 | Caroline C. Friedel, Katharina H. V. Jahn, Selina Sommer, Stephen Rudd, Hans-Werner Mewes, Igor V. Tetko: Support vector machines for separation of mixed plant?Cpathogen EST collections based on codon usage. Bioinformatics 21(8): 1383-1388 (2005) | |
| 25 | Yu Wang, Igor V. Tetko, Mark A. Hall, Eibe Frank, Axel Facius, Klaus F. X. Mayer, Hans-Werner Mewes: Gene selection from microarray data for cancer classification - a machine learning approach. Computational Biology and Chemistry 29(1): 37-46 (2005) | |
| 24 | Alexey V. Antonov, Igor V. Tetko, Denis Kosykh, Dimitrij Surmeli, Hans-Werner Mewes: Exploiting scale-free information from expression data for cancer classification. Computational Biology and Chemistry 29(4): 288-293 (2005) | |
| 23 | Stephen Rudd, Igor V. Tetko: Éclair - a web service for unravelling species origin of sequences sampled from mixed host interfaces. Nucleic Acids Research 33(Web-Server-Issue): 724-727 (2005) | |
| 2004 | ||
| 22 | Alexey V. Antonov, Igor V. Tetko, Volodymyr V. Prokopenko, Denis Kosykh, Hans-Werner Mewes: A web portal for classification of expression data using maximal margin linear programming. Bioinformatics 20(17): 3284-3285 (2004) | |
| 21 | Alexey V. Antonov, Igor V. Tetko, Michael T. Mader, Jan Budczies, Hans-Werner Mewes: Optimization models for cancer classification: extracting gene interaction information from microarray expression data. Bioinformatics 20(5): 644-652 (2004) | |
| 2003 | ||
| 20 | Alexey V. Antonov, Igor V. Tetko, Michael T. Mader, Jan Budczies, Hans-Werner Mewes: Exploiting gene interaction information from microarray expression data for cancer classification. German Conference on Bioinformatics 2003: 9-14 | |
| 2002 | ||
| 19 | Igor V. Tetko: Neural Network Studies, 4. Introduction to Associative Neural Networks. Journal of Chemical Information and Computer Sciences 42(3): 717-728 (2002) | |
| 18 | Igor V. Tetko, Vsevolod Yu. Tanchuk: Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program. Journal of Chemical Information and Computer Sciences 42(5): 1136-1145 (2002) | |
| 17 | Igor V. Tetko: Associative Neural Network. Neural Processing Letters 16(2): 187-199 (2002) | |
| 2001 | ||
| 16 | Igor V. Tetko, Vsevolod Yu. Tanchuk, Tamara N. Kasheva, Alessandro E. P. Villa: Internet Software for the Calculation of the Lipophilicity and Aqueous Solubility of Chemical Compounds. Journal of Chemical Information and Computer Sciences 41(2): 246-252 (2001) | |
| 15 | Igor V. Tetko, Vsevolod Yu. Tanchuk, Alessandro E. P. Villa: Prediction of n-Octanol/Water Partition Coefficients from PHYSPROP Database Using Artificial Neural Networks and E-State Indices. Journal of Chemical Information and Computer Sciences 41(5): 1407-1421 (2001) | |
| 14 | Igor V. Tetko, Vsevolod Yu. Tanchuk, Tamara N. Kasheva, Alessandro E. P. Villa: Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices. Journal of Chemical Information and Computer Sciences 41(6): 1488-1493 (2001) | |
| 13 | Alessandro E. P. Villa, Igor V. Tetko, Javier Iglesias: Computer assisted neurophysiological analysis of cell assemblies activity. Neurocomputing 38-40: 1025-1030 (2001) | |
| 12 | Igor V. Tetko, Alessandro E. P. Villa: Pattern grouping algorithm and de-convolution filtering of non-stationary correlated Poisson processes. Neurocomputing 38-40: 1709-1714 (2001) | |
| 2000 | ||
| 11 | Jarmo J. Huuskonen, David J. Livingstone, Igor V. Tetko: Neural Network Modeling for Estimation of Partition Coefficient Based on Atom-Type Electrotopological State Indices. Journal of Chemical Information and Computer Sciences 40(4): 947-955 (2000) | |
| 1998 | ||
| 10 | Luc Jeandenans, Michel Gautero, François Grize, Igor V. Tetko, Alessandro E. P. Villa: Computer assisted neurophysiology by a distributed JAVA program. HCC 1998: 261-272 | |
| 9 | Vasyl V. Kovalishyn, Igor V. Tetko, Alexander I. Luik, Vladyslav V. Kholodovych, Alessandro E. P. Villa, David J. Livingstone: Neural Network Studies. 3. Variable Selection in the Cascade-Correlation Learning Architecture. Journal of Chemical Information and Computer Sciences 38(4): 651-659 (1998) | |
| 8 | Igor V. Tetko, Alessandro E. P. Villa, Tatyana I. Aksenova, Walter L. Zielinski, James Brower, Elizabeth R. Collantes, William J. Welsh: Application of a Pruning Algorithm To Optimize Artificial Neural Networks for Pharmaceutical Fingerprinting. Journal of Chemical Information and Computer Sciences 38(4): 660-668 (1998) | |
| 1997 | ||
| 7 | Igor V. Tetko, Alessandro E. P. Villa: A Comparative Study of Pattern Detection Algorithm and Dynamical System Approach Using Simulated Spike Trains. ICANN 1997: 37-42 | |
| 6 | David J. Livingstone, David T. Manallack, Igor V. Tetko: Data modelling with neural networks: Advantages and limitations. Journal of Computer-Aided Molecular Design 11(2): 135-142 (1997) | |
| 5 | Igor V. Tetko, Alessandro E. P. Villa: Efficient Partition of Learning Data Sets for Neural Network Training. Neural Networks 10(8): 1361-1374 (1997) | |
| 4 | Igor V. Tetko, Alessandro E. P. Villa: An Enhancement of Generalization Ability in Cascade Correlation Algorithm by Avoidance of Overfitting/Overtraining Problem. Neural Processing Letters 6(1-2): 43-50 (1997) | |
| 3 | Igor V. Tetko, Alessandro E. P. Villa: An Efficient Partition of Training Data Set Improves Speed and Accuracy of Cascade-correlation Algorithm. Neural Processing Letters 6(1-2): 51-59 (1997) | |
| 1996 | ||
| 2 | Igor V. Tetko, Alessandro E. P. Villa, David J. Livingstone: Neural Network Studies, 2. Variable Selection. Journal of Chemical Information and Computer Sciences 36(4): 794-803 (1996) | |
| 1995 | ||
| 1 | Igor V. Tetko, David J. Livingstone, Alexander I. Luik: Neural network studies, 1. Comparison of overfitting and overtraining. Journal of Chemical Information and Computer Sciences 35(5): 826-833 (1995) | |