| Fast and accurate deep network learning by exponential linear units (elus) DA Clevert, T Unterthiner, S Hochreiter International Conference on Learning Representations (ICLR), 2015 | 3310 | 2015 |
| A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium SEQC Consortium Nature biotechnology 32 (9), 903, 2014 | 582 | 2014 |
| cn. MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate G Klambauer, K Schwarzbauer, A Mayr, DA Clevert, A Mitterecker, ... Nucleic acids research 40 (9), e69-e69, 2012 | 330 | 2012 |
| FABIA: factor analysis for bicluster acquisition S Hochreiter, U Bodenhofer, M Heusel, A Mayr, A Mitterecker, A Kasim, ... Bioinformatics 26 (12), 1520-1527, 2010 | 298 | 2010 |
| A new summarization method for Affymetrix probe level data S Hochreiter, DA Clevert, K Obermayer Bioinformatics 22 (8), 943-949, 2006 | 294 | 2006 |
| Large-scale comparison of machine learning methods for drug target prediction on ChEMBL A Mayr, G Klambauer, T Unterthiner, M Steijaert, JK Wegner, ... Chemical science 9 (24), 5441-5451, 2018 | 172 | 2018 |
| I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data W Talloen, DA Clevert, S Hochreiter, D Amaratunga, L Bijnens, S Kass, ... Bioinformatics 23 (21), 2897-2902, 2007 | 139 | 2007 |
| Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations R Winter, F Montanari, F Noé, DA Clevert Chemical science 10 (6), 1692-1701, 2019 | 120 | 2019 |
| Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures SA Munro, SP Lund, PS Pine, H Binder, DA Clevert, A Conesa, J Dopazo, ... Nature communications 5 (1), 1-10, 2014 | 87 | 2014 |
| Color duplex ultrasound and contrast-enhanced ultrasound in comparison to MS-CT in the detection of endoleak following endovascular aneurysm repair DA Clevert, N Minaifar, S Weckbach, R Kopp, G Meimarakis, M Reiser Clinical hemorheology and microcirculation 39 (1–4), 121-132, 2008 | 78 | 2008 |
| Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project B Verbist, G Klambauer, L Vervoort, W Talloen, Z Shkedy, O Thas, ... Drug discovery today 20 (5), 505-513, 2015 | 66 | 2015 |
| Experimental Study of Reinforced Concrete Assemblies under Column Removal Scenario. HS Lew, Y Bao, S Pujol, MA Sozen ACI Structural Journal 111 (4), 2014 | 66 | 2014 |
| Genome‐wide copy number alterations detection in fresh frozen and matched FFPE samples using SNP 6.0 arrays M Tuefferd, A De Bondt, I Van Den Wyngaert, W Talloen, T Verbeke, ... Genes, Chromosomes and Cancer 47 (11), 957-964, 2008 | 64 | 2008 |
| Color Doppler, power Doppler and B-flow ultrasound in the assessment of ICA stenosis: comparison with 64-MD-CT angiography DA Clevert, T Johnson, EM Jung, PM Flach, TI Strautz, G Ritter, ... European radiology 17 (8), 2149-2159, 2007 | 64 | 2007 |
| Contrast-enhanced ultrasound versus MS-CT in blunt abdominal trauma DA Clevert, S Weckbach, N Minaifar, M Stickel, M Reiser Clinical hemorheology and microcirculation 39 (1–4), 155-169, 2008 | 56 | 2008 |
| High-grade stenoses of the internal carotid artery: comparison of high-resolution contrast enhanced 3D MRA, duplex sonography and power Doppler imaging DA Clevert, T Johnson, H Michaely, EM Jung, PM Flach, TI Strautz, ... European journal of radiology 60 (3), 379-386, 2006 | 54 | 2006 |
| De novo generation of hit-like molecules from gene expression signatures using artificial intelligence O Méndez-Lucio, B Baillif, DA Clevert, D Rouquié, J Wichard Nature communications 11 (1), 1-10, 2020 | 48 | 2020 |
| Efficient Multi-Objective Molecular Optimization in a Continuous Latent Space R Winter, F Montanari, A Steffen, H Briem, F Noé, DA Clevert Chemical Science 10 (34), 8016--8024, 2019 | 40 | 2019 |
| Connecting gene expression data from connectivity map and in silico target predictions for small molecule mechanism-of-action analysis AC Ravindranath, N Perualila-Tan, A Kasim, G Drakakis, S Liggi, ... Molecular BioSystems 11 (1), 86-96, 2015 | 29 | 2015 |
| cn. FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate DA Clevert, A Mitterecker, A Mayr, G Klambauer, M Tuefferd, AD Bondt, ... Nucleic Acids Research 39 (12), e79-e79, 2011 | 29 | 2011 |
Sepp HochreiterInstitute for Machine Learning, Johannes Kepler University LinzVerified email at ml.jku.at
