A community effort to assess and improve drug sensitivity prediction algorithms JC Costello, LM Heiser, E Georgii, M Gönen, MP Menden, NJ Wang, ... Nature biotechnology 32 (12), 1202-1212, 2014 | 510 | 2014 |
Bayesian non-linear independent component analysis by multi-layer perceptrons H Lappalainen, A Honkela Advances in independent component analysis, 93-121, 2000 | 250* | 2000 |
Identifying differentially expressed transcripts from RNA-seq data with biological variation P Glaus, A Honkela, M Rattray Bioinformatics 28 (13), 1721-1728, 2012 | 208 | 2012 |
Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes JA Lees, M Vehkala, N Välimäki, SR Harris, C Chewapreecha, ... Nature communications 7 (1), 1-8, 2016 | 131 | 2016 |
Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities P Gao, A Honkela, M Rattray, ND Lawrence Bioinformatics 24 (16), i70-i75, 2008 | 116 | 2008 |
Model-based method for transcription factor target identification with limited data A Honkela, C Girardot, EH Gustafson, YH Liu, EEM Furlong, ... Proceedings of the National Academy of Sciences 107 (17), 7793-7798, 2010 | 114 | 2010 |
Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes A Honkela, T Raiko, M Kuusela, M Tornio, J Karhunen The Journal of Machine Learning Research 11, 3235-3268, 2010 | 106 | 2010 |
Nonlinear independent component analysis using ensemble learning: Experiments and discussion H Valpola, X Giannakopoulos, A Honkela, J Karhunen Proc. Second International Workshop on Independent Component Analysis and …, 2000 | 88* | 2000 |
Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays A Honkela, J Peltonen, H Topa, I Charapitsa, F Matarese, K Grote, ... Proceedings of the National Academy of Sciences 112 (42), 13115-13120, 2015 | 74 | 2015 |
Variational learning and bits-back coding: an information-theoretic view to Bayesian learning A Honkela, H Valpola IEEE transactions on Neural Networks 15 (4), 800-810, 2004 | 68 | 2004 |
A generative approach for image-based modeling of tumor growth BH Menze, K Van Leemput, A Honkela, E Konukoglu, MA Weber, ... Biennial International Conference on Information Processing in Medical …, 2011 | 61 | 2011 |
Unsupervised Variational Bayesian Learning of Nonlinear Models. A Honkela, H Valpola NIPS, 593-600, 2004 | 61 | 2004 |
On-line variational Bayesian learning A Honkela, H Valpola 4th International Symposium on Independent Component Analysis and Blind …, 2003 | 48 | 2003 |
Natural conjugate gradient in variational inference A Honkela, M Tornio, T Raiko, J Karhunen International Conference on Neural Information Processing, 305-314, 2007 | 46 | 2007 |
Nonlinear blind source separation by variational Bayesian learning H Valpola, E Oja, A Ilin, A Honkela, J Karhunen IEICE Transactions on Fundamentals of Electronics, Communications and …, 2003 | 46 | 2003 |
Gaussian process test for high-throughput sequencing time series: application to experimental evolution H Topa, Á Jónás, R Kofler, C Kosiol, A Honkela Bioinformatics 31 (11), 1762-1770, 2015 | 39 | 2015 |
Blind separation of nonlinear mixtures by variational Bayesian learning A Honkela, H Valpola, A Ilin, J Karhunen Digital Signal Processing 17 (5), 914-934, 2007 | 35 | 2007 |
Fast and accurate approximate inference of transcript expression from RNA-seq data J Hensman, P Papastamoulis, P Glaus, A Honkela, M Rattray Bioinformatics 31 (24), 3881-3889, 2015 | 34 | 2015 |
Exploration and retrieval of whole-metagenome sequencing samples S Seth, N Välimäki, S Kaski, A Honkela Bioinformatics 30 (17), 2471-2479, 2014 | 31 | 2014 |
Accelerating cyclic update algorithms for parameter estimation by pattern searches A Honkela, H Valpola, J Karhunen Neural Processing Letters 17 (2), 191-203, 2003 | 31 | 2003 |