| A statistical framework for genomic data fusion GRG Lanckriet, T De Bie, N Cristianini, MI Jordan, WS Noble Bioinformatics 20 (16), 2626-2635, 2004 | 784 | 2004 |
| CAFE: a computational tool for the study of gene family evolution T De Bie, N Cristianini, JP Demuth, MW Hahn Bioinformatics 22 (10), 1269-1271, 2006 | 480 | 2006 |
| The evolution of mammalian gene families JP Demuth, T De Bie, JE Stajich, N Cristianini, MW Hahn PloS one 1 (1), 2006 | 316 | 2006 |
| Flu detector-tracking epidemics on Twitter V Lampos, T De Bie, N Cristianini Joint European conference on machine learning and knowledge discovery in …, 2010 | 282 | 2010 |
| Estimating the tempo and mode of gene family evolution from comparative genomic data MW Hahn, T De Bie, JE Stajich, C Nguyen, N Cristianini Genome Research 15 (8), 1153-1160, 2005 | 222 | 2005 |
| Kernel-based data fusion for gene prioritization T De Bie, LC Tranchevent, LMM van Oeffelen, Y Moreau Bioinformatics 23 (13), i125-i132, 2007 | 171 | 2007 |
| Eigenproblems in pattern recognition T De Bie, N Cristianini, R Rosipal Handbook of Geometric Computing, 129-167, 2005 | 170* | 2005 |
| Convex methods for transduction T De Bie, N Cristianini Advances in neural information processing systems 16: proceedings of the …, 2004 | 147* | 2004 |
| Maximum entropy models and subjective interestingness: an application to tiles in binary databases T De Bie Data Mining and Knowledge Discovery, 1-40, 2011 | 131 | 2011 |
| Inferring transcriptional modules from ChIP-chip, motif and microarray data K Lemmens, T Dhollander, T De Bie, P Monsieurs, K Engelen, B Smets, ... Genome biology 7 (5), R37, 2006 | 131 | 2006 |
| An information theoretic framework for data mining T De Bie Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 106 | 2011 |
| An end-to-end machine learning system for harmonic analysis of music Y Ni, M Mcvicar, R Santos-Rodriguez, T De Bie IEEE Transactions on Audio, Speech, and Language Processing 20 (6), 2012 | 74 | 2012 |
| Automatic chord estimation from audio: A review of the state of the art M McVicar, R Santos-Rodríguez, Y Ni, T De Bie IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (2), 556-575, 2014 | 72 | 2014 |
| Semi-supervised learning using semi-definite programming T De Bie, N Cristianini Semi-supervised learning. MIT Press, Cambridge-Massachussets, 2006 | 70 | 2006 |
| MINI: Mining informative non-redundant itemsets A Gallo, T De Bie, N Cristianini Knowledge Discovery in Databases: PKDD 2007, 438-445, 2007 | 69 | 2007 |
| Research methods in the age of digital journalism: Massive-scale automated analysis of news-content—topics, style and gender I Flaounas, O Ali, T Lansdall-Welfare, T De Bie, N Mosdell, J Lewis, ... Digital journalism 1 (1), 102-116, 2013 | 65 | 2013 |
| An information-theoretic approach to finding informative noisy tiles in binary databases KN Kontonasios, T De Bie | 65 | 2010 |
| DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli K Lemmens, T De Bie, T Dhollander, SC De Keersmaecker, IM Thijs, ... Genome Biol 10 (3), R27, 2009 | 61 | 2009 |
| Fast SDP relaxations of graph cut clustering, transduction, and other combinatorial problems T De Bie, N Cristianini The Journal of Machine Learning Research 7, 1409-1436, 2006 | 61 | 2006 |
| Learning from general label constraints T De Bie, J Suykens, B De Moor Structural, Syntactic, and Statistical Pattern Recognition, 671-679, 2004 | 60 | 2004 |
Nello CristianiniUniversity of BristolVerified email at bristol.ac.uk
