| A systematic comparison of chloroplast genome assembly tools JA Freudenthal, S Pfaff, N Terhoeven, A Korte, MJ Ankenbrand, F Förster Genome Biology 21, 1-21, 2020 | 73 | 2020 |
| AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana M Togninalli, Ü Seren, JA Freudenthal, JG Monroe, D Meng, M Nordborg, ... Nucleic acids research 48 (D1), D1063-D1068, 2020 | 68 | 2020 |
| Using local convolutional neural networks for genomic prediction T Pook, J Freudenthal, A Korte, H Simianer Frontiers in genetics 11, 561497, 2020 | 42 | 2020 |
| Phantom epistasis in genomic selection: on the predictive ability of epistatic models MF Schrauf, JWR Martini, H Simianer, G de Los Campos, R Cantet, ... G3: Genes, Genomes, Genetics 10 (9), 3137-3145, 2020 | 33 | 2020 |
| Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions M John, MJ Ankenbrand, C Artmann, JA Freudenthal, A Korte, DG Grimm Bioinformatics 38 (Supplement_2), ii5-ii12, 2022 | 20 | 2022 |
| GWAS-Flow: A GPU accelerated framework for efficient permutation based genome-wide association studies JA Freudenthal, MJ Ankenbrand, DG Grimm, A Korte BioRxiv, 783100, 2019 | 17 | 2019 |
| The landscape of chloroplast genome assembly tools JA Freudenthal, S Pfaff, N Terhoeven, A Korte, MJ Ankenbrand, F Förster bioRxiv 665869, 2019 | 8 | 2019 |
| Quantitative genetics from genome assemblies to neural network aided omics-based prediction of complex traits JA Freudenthal PQDT-Global, 2020 | 1 | 2020 |
| Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions (vol 38, pg ii5, 2022) M John, MJ Ankenbrand, C Artmann, JA Freudenthal, A Korte, DG Grimm BIOINFORMATICS 38 (22), 5149-5149, 2022 | | 2022 |
Arthur KorteCenter of Computational and Theoretical Biology, University WuerzburgVerified email at uni-wuerzburg.de