2008 |
33 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Igor V. Tetko,
Axel Facius,
Andreas Ruepp,
Hans-Werner Mewes:
Super paramagnetic clustering of protein sequences.
BMC Bioinformatics 6: 82 (2005) |
27 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Alessandro E. P. Villa,
Igor V. Tetko,
Javier Iglesias:
Computer assisted neurophysiological analysis of cell assemblies activity.
Neurocomputing 38-40: 1025-1030 (2001) |
12 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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) |