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ORCIDBart De Moor
B. L. R. De Moor
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- affiliation: Catholic University of Leuven, Belgium
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2020 – today
- 2020
[j161]João Pita Costa, Marko Grobelnik, Flavio Fuart, Luka Stopar, Gorka Epelde, Scott Fischaber, Piotr Poliwoda, Debbie Rankin, Jonathan G. Wallace, Michaela M. Black, Raymond Bond, Maurice D. Mulvenna, Dale Weston, Paul Carlin, Roberto Bilbao, Gorana Nikolic, Xi Shi, Bart De Moor, Minna Pikkarainen, Jarmo Pääkkönen, Anthony Staines, Regina Connolly, Paul Davis:
Meaningful Big Data Integration for a Global COVID-19 Strategy. IEEE Comput. Intell. Mag. 15(4): 51-61 (2020)- [j160]Bart De Moor:
Least squares optimal realisation of autonomous LTI systems is an eigenvalue problem. Commun. Inf. Syst. 20(2): 163-207 (2020) - [j159]Gorka Epelde, Andoni Beristain, Roberto Álvarez, Mónica Arrúe, Iker Ezkerra, Oihana Belar, Roberto Bilbao, Gorana Nikolic, Xi Shi, Bart De Moor, Maurice D. Mulvenna:
Quality of data measurements in the big data era: Lessons learned from MIDAS project. IEEE Instrum. Meas. Mag. 23(7): 18-24 (2020) - [c114]Hannes De Meulemeester, Bart De Moor:
Unsupervised Embeddings for Categorical Variables. IJCNN 2020: 1-8 - [i17]Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens:
The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks. CoRR abs/2006.09096 (2020)
2010 – 2019
- 2019
- [j158]Christof Vermeersch
, Bart De Moor:
Globally Optimal Least-Squares ARMA Model Identification is an Eigenvalue Problem. IEEE Control. Syst. Lett. 3(4): 1062-1067 (2019) - [c113]Bart De Moor:
Least squares realization of LTI models is an eigenvalue problem. ECC 2019: 2270-2275 - 2018
- [j157]Oliver Lauwers, Oscar Mauricio Agudelo, Bart De Moor:
A Multiple-Input Multiple-Output Cepstrum. IEEE Control. Syst. Lett. 2(2): 272-277 (2018) - [j156]Philippe Dreesen, Kim Batselier, Bart De Moor:
Multidimensional realisation theory and polynomial system solving. Int. J. Control 91(12): 2692-2704 (2018) - [c112]Bob Vergauwen, Oscar Mauricio Agudelo, Bart De Moor:
Order estimation of two dimensional systems based on rank decisions. CDC 2018: 1451-1456 - [c111]Bart De Moor, Yasamin Mostofi, Maryam Kamgarpour, Zdenko Kovacic, Maja Cepanec, Airlie Chapman, Mehran Mesbahi:
Plenary Lectures. MED 2018 - [i16]Oliver Lauwers, Oscar Mauricio Agudelo, Bart De Moor:
A Multiple-Input Multiple-Output Cepstrum. CoRR abs/1803.03080 (2018) - [i15]Oliver Lauwers, Bart De Moor:
Applicability and interpretation of the deterministic weighted cepstral distance. CoRR abs/1803.03104 (2018) - [i14]Philippe Dreesen, Kim Batselier, Bart De Moor:
Multidimensional Realization Theory and Polynomial System Solving. CoRR abs/1805.02253 (2018) - 2017
- [j155]Oliver Lauwers, Bart De Moor:
A Time Series Distance Measure for Efficient Clustering of Input/Output Signals by Their Underlying Dynamics. IEEE Control. Syst. Lett. 1(2): 286-291 (2017) - [i13]Oliver Lauwers, Bart De Moor:
A time series distance measure for efficient clustering of input output signals by their underlying dynamics. CoRR abs/1703.01923 (2017) - 2015
- [j154]Dusan Popovic, Alejandro Sifrim, Jesse Davis, Yves Moreau, Bart De Moor:
Problems with the nested granularity of feature domains in bioinformatics: the eXtasy case. BMC Bioinform. 16(S-4): S2 (2015) - [j153]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
A robust ensemble approach to learn from positive and unlabeled data using SVM base models. Neurocomputing 160: 73-84 (2015) - [c110]Antoine Vandermeersch, Bart De Moor:
A SVD approach to multivariate polynomial optimization problems. CDC 2015: 7232-7237 - [c109]Mandar Chandorkar, Raghvendra Mall, Oliver Lauwers, Johan A. K. Suykens, Bart De Moor:
Fixed-Size Least Squares Support Vector Machines: Scala Implementation for Large Scale Classification. SSCI 2015: 522-528 - [c108]Dusan Popovic, Jesse Davis, Alejandro Sifrim, Bart De Moor:
A Note on the Evaluation of Mutation Prioritization Algorithms. SSCI 2015: 1351-1357 - [i12]Marc Claesen, Bart De Moor:
Hyperparameter Search in Machine Learning. CoRR abs/1502.02127 (2015) - [i11]Marc Claesen, Jesse Davis, Frank De Smet, Bart De Moor:
Assessing binary classifiers using only positive and unlabeled data. CoRR abs/1504.06837 (2015) - [i10]Marc Claesen, Frank De Smet, Pieter Gillard, Chantal Mathieu, Bart De Moor:
Building Classifiers to Predict the Start of Glucose-Lowering Pharmacotherapy Using Belgian Health Expenditure Data. CoRR abs/1504.07389 (2015) - 2014
- [j152]Minta Thomas, Kris De Brabanter, Bart De Moor:
New Bandwidth Selection Criterion for Kernel PCA: Approach to Dimensionality Reduction and Classification Problems. BMC Bioinform. 15: 137 (2014) - [j151]Minta Thomas, Kris De Brabanter, Johan A. K. Suykens, Bart De Moor:
Predicting breast cancer using an expression values weighted clinical classifier. BMC Bioinform. 15: 6603 (2014) - [j150]Rocco Langone, Oscar Mauricio Agudelo, Bart De Moor, Johan A. K. Suykens:
Incremental kernel spectral clustering for online learning of non-stationary data. Neurocomputing 139: 246-260 (2014) - [j149]Kim Batselier, Philippe Dreesen, Bart De Moor:
A fast recursive orthogonalization scheme for the Macaulay matrix. J. Comput. Appl. Math. 267: 20-32 (2014) - [j148]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
EnsembleSVM: a library for ensemble learning using support vector machines. J. Mach. Learn. Res. 15(1): 141-145 (2014) - [j147]Kim Batselier, Philippe Dreesen, Bart De Moor:
The Canonical Decomposition of Cnd and Numerical Gröbner and Border Bases. SIAM J. Matrix Anal. Appl. 35(4): 1242-1264 (2014) - [j146]Minta Thomas, Anneleen Daemen, Bart De Moor:
Maximum Likelihood Estimation ofGEVD: Applications in Bioinformatics. IEEE ACM Trans. Comput. Biol. Bioinform. 11(4): 673-680 (2014) - [c107]Dusan Popovic, Charalampos N. Moschopoulos, Ryo Sakai, Alejandro Sifrim, Jan Aerts, Yves Moreau, Bart De Moor:
A Self-Tuning Genetic Algorithm with Applications in Biomarker Discovery. CBMS 2014: 233-238 - [c106]Charalampos N. Moschopoulos, Dusan Popovic, Rocco Langone, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
Gene interaction networks boost genetic algorithm performance in biomarker discovery. MCDM 2014: 144-149 - [i9]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models. CoRR abs/1402.3144 (2014) - [i8]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
Fast Prediction with SVM Models Containing RBF Kernels. CoRR abs/1403.0736 (2014) - [i7]Marc Claesen, Frank De Smet, Johan A. K. Suykens, Bart De Moor:
EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines. CoRR abs/1403.0745 (2014) - [i6]Marc Claesen, Jaak Simm, Dusan Popovic, Yves Moreau, Bart De Moor:
Easy Hyperparameter Search Using Optunity. CoRR abs/1412.1114 (2014) - 2013
- [j145]Adeshola A. Adefioye, Xinhai Liu, Bart De Moor:
Multi-view spectral clustering and its chemical application. Int. J. Comput. Biol. Drug Des. 6(1/2): 32-49 (2013) - [j144]Kris De Brabanter, Jos De Brabanter, Bart De Moor, Irène Gijbels:
Derivative estimation with local polynomial fitting. J. Mach. Learn. Res. 14(1): 281-301 (2013) - [j143]Kim Batselier, Philippe Dreesen, Bart De Moor:
The Geometry of Multivariate Polynomial Division and Elimination. SIAM J. Matrix Anal. Appl. 34(1): 102-125 (2013) - [j142]Diana Ugryumova, Gerd Vandersteen, Bart Huyck, Filip Logist, Jan F. M. Van Impe, Bart De Moor:
Identification of a Noninsulated Distillation Column From Transient Response Data. IEEE Trans. Instrum. Meas. 62(5): 1382-1391 (2013) - [j141]Xinhai Liu, Shuiwang Ji, Wolfgang Glänzel, Bart De Moor:
Multiview Partitioning via Tensor Methods. IEEE Trans. Knowl. Data Eng. 25(5): 1056-1069 (2013) - [c105]Dusan Popovic, Alejandro Sifrim, Yves Moreau, Bart De Moor:
eXtasy simplified-towards opening the black box. BIBM 2013: 24-28 - [c104]Charalampos N. Moschopoulos, Dusan Popovic, Alejandro Sifrim, Grigorios N. Beligiannis, Bart De Moor, Yves Moreau:
A Genetic Algorithm for Pancreatic Cancer Diagnosis. EANN (2) 2013: 222-230 - [c103]Dusan Popovic, Alejandro Sifrim, Charalampos N. Moschopoulos, Yves Moreau, Bart De Moor:
A Hybrid Approach to Feature Ranking for Microarray Data Classification. EANN (2) 2013: 241-248 - [c102]Bart Huyck, Jos De Brabanter, Bart De Moor, Jan F. M. Van Impe, Filip Logist:
Model predictive control of a pilot-scale distillation column using a programmable automation controller. ECC 2013: 1053-1058 - 2012
- [j140]Anneleen Daemen, Dirk Timmerman, Thierry Van den Bosch, Cecilia Bottomley, Emma Kirk, Caroline Van Holsbeke, Lil Valentin, Tom Bourne, Bart De Moor:
Improved modeling of clinical data with kernel methods. Artif. Intell. Medicine 54(2): 103-114 (2012) - [j139]Ernesto Iacucci, Léon-Charles Tranchevent, Dusan Popovic, Georgios A. Pavlopoulos, Bart De Moor, Reinhard Schneider, Yves Moreau:
ReLiance: a machine learning and literature-based prioritization of receptor - ligand pairings. Bioinform. 28(18): 569-574 (2012) - [j138]Daniela Börnigen, Léon-Charles Tranchevent, Francisco Bonachela Capdevila, Koenraad Devriendt, Bart De Moor, Patrick De Causmaecker, Yves Moreau:
An unbiased evaluation of gene prioritization tools. Bioinform. 28(23): 3081-3088 (2012) - [j137]Ernesto Iacucci, Léon-Charles Tranchevent, Dusan Popovic, Georgios A. Pavlopoulos, Bart De Moor, Reinhard Schneider, Yves Moreau:
A bioinformatics e-dating story: computational prediction and prioritization of receptor-ligand pairs. BMC Bioinform. 13(S-18): A7 (2012) - [j136]Shi Yu, Léon-Charles Tranchevent, Xinhai Liu, Wolfgang Glänzel, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
Optimized Data Fusion for Kernel k-Means Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 34(5): 1031-1039 (2012) - [j135]Kris De Brabanter, Peter Karsmakers, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Confidence bands for least squares support vector machine classifiers: A regression approach. Pattern Recognit. 45(6): 2280-2287 (2012) - [j134]Xinhai Liu, Wolfgang Glänzel, Bart De Moor:
Optimal and hierarchical clustering of large-scale hybrid networks for scientific mapping. Scientometrics 91(2): 473-493 (2012) - [c101]Maarten Breckpot, Oscar Mauricio Agudelo, Bart De Moor:
Model Predictive Control applied to a river system with two reaches. CDC 2012: 4549-4554 - [c100]Kim Batselier, Philippe Dreesen, Bart De Moor:
maximum likelihood estimation and polynomial system solving. ESANN 2012 - [c99]Kris De Brabanter, Bart De Moor:
Deconvolution in nonparametric statistics. ESANN 2012 - [c98]Philippe Dreesen, Kim Batselier, Bart De Moor:
Weighted/Structured Total Least Squares problems and polynomial system solving. ESANN 2012 - [c97]Dries Geebelen, Kim Batselier, Philippe Dreesen, Marco Signoretto, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Joint Regression and Linear Combination of Time Series for Optimal Prediction. ESANN 2012 - [c96]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor:
Robustness of kernel based regression: Influence and weight functions. IJCNN 2012: 1-8 - [c95]Dusan Popovic, Alejandro Sifrim, Georgios A. Pavlopoulos, Yves Moreau, Bart De Moor:
A Simple Genetic Algorithm for Biomarker Mining. PRIB 2012: 222-232 - [c94]Ernesto Iacucci, Dusan Popovic, Georgios A. Pavlopoulos, Léon-Charles Tranchevent, Marijke Bauters, Bart De Moor, Yves Moreau:
Towards Better Prioritization of Epigenetically Modified DNA Regions. SETN 2012: 270-277 - 2011
- [b3]Shi Yu, Léon-Charles Tranchevent, Bart De Moor, Yves Moreau:
Kernel-based Data Fusion for Machine Learning - Methods and Applications in Bioinformatics and Text Mining. Studies in Computational Intelligence 345, Springer 2011, ISBN 978-3-642-19405-4, pp. 1-208 - [j133]Léon-Charles Tranchevent, Francisco Bonachela Capdevila, Daniela Nitsch, Bart De Moor, Patrick De Causmaecker, Yves Moreau:
A guide to web tools to prioritize candidate genes. Briefings Bioinform. 12(1): 22-32 (2011) - [j132]Shi Yu, Xinhai Liu, Léon-Charles Tranchevent, Wolfgang Glänzel, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
Optimized data fusion for K-means Laplacian clustering. Bioinform. 27(1): 118-126 (2011) - [j131]Ernesto Iacucci, Fabian Ojeda, Bart De Moor, Yves Moreau:
Predicting Receptor-Ligand Pairs through Kernel Learning. BMC Bioinform. 12: 336 (2011) - [j130]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Kernel Regression in the Presence of Correlated Errors. J. Mach. Learn. Res. 12: 1955-1976 (2011) - [j129]Xinhai Liu, Wolfgang Glänzel, Bart De Moor:
Hybrid clustering of multi-view data via Tucker-2 model and its application. Scientometrics 88(3): 819-839 (2011) - [j128]Marco Signoretto, Raf Van de Plas, Bart De Moor, Johan A. K. Suykens:
Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data. IEEE Signal Process. Lett. 18(7): 403-406 (2011) - [j127]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression. IEEE Trans. Neural Networks 22(1): 110-120 (2011) - [c93]Oscar Mauricio Agudelo, Oscar Barrero, Viaene Peter, Bart De Moor:
Assimilation of ozone measurements in the air quality model AURORA by using the Ensemble Kalman Filter. CDC-ECE 2011: 4430-4435 - 2010
- [j126]Shi Yu, Léon-Charles Tranchevent, Bart De Moor, Yves Moreau:
Gene prioritization and clustering by multi-view text mining. BMC Bioinform. 11: 28 (2010) - [j125]Shi Yu, Tillmann Falck, Anneleen Daemen, Léon-Charles Tranchevent, Johan A. K. Suykens, Bart De Moor, Yves Moreau:
L2-norm multiple kernel learning and its application to biomedical data fusion. BMC Bioinform. 11: 309 (2010) - [j124]Daniela Nitsch, Joana P. Gonçalves, Fabian Ojeda, Bart De Moor, Yves Moreau:
Candidate gene prioritization by network analysis of differential expression using machine learning approaches. BMC Bioinform. 11: 460 (2010) - [j123]Julian Bonilla Alarcon, Moritz Diehl, Filip Logist, Bart De Moor, Jan F. M. Van Impe:
An automatic initialization procedure in parameter estimation problems with parameter-affine dynamic models. Comput. Chem. Eng. 34(6): 953-964 (2010) - [j122]Kris De Brabanter, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Optimized fixed-size kernel models for large data sets. Comput. Stat. Data Anal. 54(6): 1484-1504 (2010) - [j121]Toni Barjas Blanco, Mark Cannon, Bart De Moor:
On efficient computation of low-complexity controlled invariant sets for uncertain linear systems. Int. J. Control 83(7): 1339-1346 (2010) - [j120]Xinhai Liu, Shi Yu, Frizo A. L. Janssens, Wolfgang Glänzel, Yves Moreau, Bart De Moor:
Weighted hybrid clustering by combining text mining and bibliometrics on a large-scale journal database. J. Assoc. Inf. Sci. Technol. 61(6): 1105-1119 (2010) - [c92]Oscar Mauricio Agudelo, Jairo Jose Espinosa, Bart De Moor:
Reduction of the computational burden of POD models with polynomial nonlinearities. CDC 2010: 3457-3462 - [c91]Maarten Breckpot, Toni Barjas Blanco, Bart De Moor:
Flood control of rivers with nonlinear model predictive control and moving horizon estimation. CDC 2010: 6107-6112 - [c90]Tillmann Falck, Johan A. K. Suykens, Bart De Moor:
Linear parametric noise models for Least Squares Support Vector Machines. CDC 2010: 6389-6394 - [c89]Tillmann Falck, Johan A. K. Suykens, Johan Schoukens, Bart De Moor:
Nuclear norm regularization for overparametrized Hammerstein systems. CDC 2010: 7202-7207 - [c88]Fabian Ojeda, Tillmann Falck, Bart De Moor, Johan A. K. Suykens:
Polynomial componentwise LS-SVM: Fast variable selection using low rank updates. IJCNN 2010: 1-7 - [c87]Xinhai Liu, Lieven De Lathauwer, Frizo A. L. Janssens, Bart De Moor:
Hybrid Clustering of Multiple Information Sources via HOSVD. ISNN (2) 2010: 337-345 - [c86]Fabian Ojeda, Marco Signoretto, Raf Van de Plas, Etienne Waelkens, Bart De Moor, Johan A. K. Suykens:
Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging. PRIB 2010: 325-334
2000 – 2009
- 2009
- [j119]Hong Sun, Karen Lemmens, Tim Van den Bulcke, Kristof Engelen, Bart De Moor, Kathleen Marchal:
ViTraM: visualization of transcriptional modules. Bioinform. 25(18): 2450-2451 (2009) - [j118]Joke Allemeersch, Steven Van Vooren, Femke Hannes, Bart De Moor, Joris Robert Vermeesch, Yves Moreau:
An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH. BMC Bioinform. 10: 380 (2009) - [j117]Hong Sun, Tijl De Bie, Valerie Storms, Qiang Fu, Thomas Dhollander, Karen Lemmens, Annemieke Verstuyf, Bart De Moor, Kathleen Marchal:
ModuleDigger: an itemset mining framework for the detection of cis-regulatory modules. BMC Bioinform. 10(S-1) (2009) - [j116]Frizo A. L. Janssens, Lin Zhang, Bart De Moor, Wolfgang Glänzel:
Hybrid clustering for validation and improvement of subject-classification schemes. Inf. Process. Manag. 45(6): 683-702 (2009) - [j115]Oscar Mauricio Agudelo, Michel Baes, Jairo Jose Espinosa, Moritz Diehl, Bart De Moor:
Positive Polynomial Constraints for POD-based Model Predictive Controllers. IEEE Trans. Autom. Control. 54(5): 988-999 (2009) - [j114]Kristiaan Pelckmans, Jos De Brabanter, Johan A. K. Suykens, Bart De Moor:
Least conservative support and tolerance tubes. IEEE Trans. Inf. Theory 55(8): 3799-3806 (2009) - [c85]Niels Haverbeke, Moritz Diehl, Bart De Moor:
A structure exploiting interior-point method for moving horizon estimation. CDC 2009: 1273-1278 - [c84]Julian Bonilla Alarcon, Moritz Diehl, Filip Logist, Bart De Moor, Jan F. M. Van Impe:
A convex approximation for parameter estimation involving parameter-affine dynamic models. CDC 2009: 4670-4675 - [c83]Tillmann Falck, Johan A. K. Suykens, Bart De Moor:
Robustness analysis for Least Squares kernel based regression: an optimization approach. CDC 2009: 6774-6779 - [c82]Oscar Mauricio Agudelo, Jairo José Espinosa, Bart De Moor:
Acceleration of nonlinear POD models: A neural network approach. ECC 2009: 1547-1552 - [c81]Filip Logist, Bart Huyck, M. Fabré, M. Verwerft, Bert Pluymers, J. De Brabanter, Bart De Moor, Jan F. M. Van Impe:
Identification and control of a pilot scale binary distillation column. ECC 2009: 4659-4664 - [c80]Kris De Brabanter, Kristiaan Pelckmans, Jos De Brabanter, Michiel Debruyne, Johan A. K. Suykens, Mia Hubert, Bart De Moor:
Robustness of Kernel Based Regression: A Comparison of Iterative Weighting Schemes. ICANN (1) 2009: 100-110 - [c79]Carlos Alzate, Marcelo Espinoza, Bart De Moor, Johan A. K. Suykens:
Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering. ICANN (2) 2009: 315-324 - [c78]Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janssens, Bart De Moor, Wolfgang Glänzel:
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis. ICDM Workshops 2009: 521-526 - [c77]Hong Sun, Tim Van den Bulcke, Bart De Moor, Karen Lemmens, Kristof Engelen, Kathleen Marchal:
Layout and Post-Processing of Transcriptional Modules. IJCBS 2009: 116-121 - [c76]Anneleen Daemen, Olivier Gevaert, Karin Leunen, Eric Legius, Ignace Vergote, Bart De Moor:
Supervised Classification of Array CGH Data with HMM-Based Feature Selection. Pacific Symposium on Biocomputing 2009: 468-479 - [c75]Xinhai Liu, Shi Yu, Yves Moreau, Bart De Moor, Wolfgang Glänzel, Frizo A. L. Janssens:
Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets. SDM 2009: 49-60 - [p2]Ben Van Calster, Olivier Gevaert, Caroline Van Holsbeke, Bart De Moor, Sabine Van Huffel, Dirk Timmerman:
Clinical decision support for ovarian tumor diagnosis using Bayesian models: Results from the IOTA study. Computational Intelligence and Bioengineering 2009: 111-128 - 2008
- [j113]Koenraad Van Leemput, Tim Van den Bulcke, Thomas Dhollander, Bart De Moor, Kathleen Marchal, Piet van Remortel:
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data. Artif. Life 14(1): 49-63 (2008) - [j112]Joris Vertommen, Frizo A. L. Janssens, Bart De Moor, Joost R. Duflou:
Multiple-vector user profiles in support of knowledge sharing. Inf. Sci. 178(17): 3333-3346 (2008) - [j111]Victor Rodriguez, Frizo A. L. Janssens, Koenraad Debackere, Bart De Moor:
On material transfer agreements and visibility of researchers in biotechnology. J. Informetrics 2(1): 89-100 (2008) - [j110]Léon-Charles Tranchevent, Roland Barriot, Shi Yu, Steven Van Vooren, Peter Van Loo, Bert Coessens, Bart De Moor, Stein Aerts, Yves Moreau:
ENDEAVOUR update: a web resource for gene prioritization in multiple species. Nucleic Acids Res. 36(Web-Server-Issue): 377-384 (2008) - [j109]Fabian Ojeda, Johan A. K. Suykens, Bart De Moor:
Low rank updated LS-SVM classifiers for fast variable selection. Neural Networks 21(2-3): 437-449 (2008) - [j108]Frizo A. L. Janssens, Wolfgang Glänzel, Bart De Moor:
A hybrid mapping of information science. Scientometrics 75(3): 607-631 (2008) - [j107]Bart Vanluyten, Jan C. Willems, Bart De Moor:
Equivalence of state representations for hidden Markov models. Syst. Control. Lett. 57(5): 410-419 (2008) - [c74]Oscar Mauricio Agudelo, Jairo Jose Espinosa, Bart De Moor:
Algorithm for reducing the number of constraints of POD-based predictive controllers. CDC 2008: 4743-4748 - [c73]Julian Bonilla Alarcon, Moritz Diehl, Bart De Moor, Jan F. M. Van Impe:
A nonlinear least squares estimation procedure without initial parameter guesses. CDC 2008: 5519-5524 - [c72]Shi Yu, Steven Van Vooren, Léon-Charles Tranchevent, Bart De Moor, Yves Moreau:
Comparison of vocabularies, representations and ranking algorithms for gene prioritization by text mining. ECCB 2008: 119-125 - [c71]Anneleen Daemen, Olivier Gevaert, Karin Leunen, Vanessa Vanspauwen, Geneviève Michils, Eric Legius, Ignace Vergote, Bart De Moor:
Classification of Sporadic and BRCA1 Ovarian Cancer Based on a Genome-Wide Study of Copy Number Variations. KES (2) 2008: 165-172 - [c70]Anneleen Daemen, Olivier Gevaert, Tijl De Bie, Annelies Debucquoy, Jean-Pascal Machiels, Bart De Moor, Karin Haustermans:
Integrating Microarray and Proteomics Data to Predict the Response of Cetuximab in Patients with Rectal Cancer. Pacific Symposium on Biocomputing 2008: 166-177 - [c69]O. Gaevert, Steven Van Vooren, Bart De Moor:
Integration of Microarray and Textual Data Improves the Prognosis Prediction of Breast, Lung, and Ovarian Cancer Patients. Pacific Symposium on Biocomputing 2008: 279-290 - [c68]Raf Van de Plas, Bart De Moor, Etienne Waelkens:
Discrete wavelet transform-based multivariate exploration of tissue via imaging mass spectrometry. SAC 2008: 1307-1308 - 2007
- [j106]Steven Gillijns, Bart De Moor:
Unbiased minimum-variance input and state estimation for linear discrete-time systems. Autom. 43(1): 111-116 (2007) - [j105]Steven Gillijns, Bart De Moor:
Unbiased minimum-variance input and state estimation for linear discrete-time systems with direct feedthrough. Autom. 43(5): 934-937 (2007) - [j104]