| Critical assessment of automated flow cytometry data analysis techniques N Aghaeepour, G Finak, H Hoos, TR Mosmann, R Brinkman, R Gottardo, ... Nature Methods, 2013 | 687 | 2013 |
| Using intron position conservation for homology-based gene prediction J Keilwagen, M Wenk, JL Erickson, MH Schattat, J Grau, F Hartung Nucleic acids research 44 (9), e89-e89, 2016 | 533 | 2016 |
| Evaluation of methods for modeling transcription factor sequence specificity MT Weirauch, A Cote, R Norel, M Annala, Y Zhao, TR Riley, ... Nature Biotechnology, 2013 | 415 | 2013 |
| PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R J Grau, I Grosse, J Keilwagen Bioinformatics 31 (15), 2595-2597, 2015 | 358 | 2015 |
| GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data. J Keilwagen, F Hartung, J Grau Methods in molecular biology (Clifton, NJ) 1962, 161-177, 2019 | 270 | 2019 |
| Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi J Keilwagen, F Hartung, M Paulini, SO Twardziok, J Grau BMC Bioinformatics 19 (1), 189, 2018 | 261 | 2018 |
| Identification of transcription factor binding sites with variable-order Bayesian networks I Ben-Gal, A Shani, A Gohr, J Grau, S Arviv, A Shmilovici, S Posch, ... Bioinformatics 21 (11), 2657-2666, 2005 | 243 | 2005 |
| Area under Precision-Recall Curves for Weighted and Unweighted Data J Keilwagen, I Grosse, J Grau PLOS ONE 9 (3), e92209, 2014 | 216 | 2014 |
| Recognition of AvrBs3-like proteins is mediated by specific binding to promoters of matching pepper Bs3 alleles P Römer, T Strauss, S Hahn, H Scholze, R Morbitzer, J Grau, U Bonas, ... Plant physiology 150 (4), 1697-1712, 2009 | 143 | 2009 |
| Computational Predictions Provide Insights into the Biology of TAL Effector Target Sites J Grau, A Wolf, M Reschke, U Bonas, S Posch, J Boch PLOS Computational Biology 9 (3), e1002962, 2013 | 124 | 2013 |
| TALENoffer: genome-wide TALEN off-target prediction J Grau, J Boch, S Posch Bioinformatics 29 (22), 2931-2932, 2013 | 121 | 2013 |
| Accurate prediction of cell type-specific transcription factor binding J Keilwagen, S Posch, J Grau Genome Biology 20 (1), 9, 2019 | 115 | 2019 |
| AnnoTALE: bioinformatics tools for identification, annotation, and nomenclature of TALEs from Xanthomonas genomic sequences J Grau, M Reschke, A Erkes, J Streubel, RD Morgan, GG Wilson, ... Scientific Reports 6, 21077, 2016 | 109 | 2016 |
| Varying levels of complexity in transcription factor binding motifs J Keilwagen, J Grau Nucleic acids research 43 (18), e119-e119, 2015 | 78 | 2015 |
| DiffLogo: a comparative visualization of sequence motifs M Nettling, H Treutler, J Grau, J Keilwagen, S Posch, I Grosse BMC bioinformatics 16 (1), 387, 2015 | 71 | 2015 |
| De-novo discovery of differentially abundant transcription factor binding sites including their positional preference J Keilwagen, J Grau, IA Paponov, S Posch, M Strickert, I Grosse PLoS Computational Biology 7 (2), e1001070, 2011 | 67 | 2011 |
| A TAL effector repeat architecture for frameshift binding A Richter, J Streubel, C Blücher, B Szurek, M Reschke, J Grau, J Boch Nature communications 5, 3447, 2014 | 63 | 2014 |
| A general approach for discriminative de novo motif discovery from high-throughput data J Grau, S Posch, I Grosse, J Keilwagen Nucleic acids research 41 (21), e197-e197, 2013 | 59 | 2013 |
| Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study G Ambrosini, I Vorontsov, D Penzar, R Groux, O Fornes, DD Nikolaeva, ... Genome Biology 21 (1), 1-18, 2020 | 57 | 2020 |
| Jstacs: A Java Framework for Statistical Analysis and Classification of Biological Sequences J Grau, J Keilwagen, A Gohr, B Haldemann, S Posch, I Grosse The Journal of Machine Learning Research 98888, 1967-1971, 2012 | 57 | 2012 |
Jens KeilwagenJulius Kuehn-InstituteVerified email at julius-kuehn.de
