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Jan Freudenthal
Jan Freudenthal
Center of Computational and Theoretical Biology
Verified email at uni-wuerzburg.de
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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
382020
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
332020
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
202020
Using local convolutional neural networks for genomic prediction
T Pook, J Freudenthal, A Korte, H Simianer
Frontiers in genetics 11, 561497, 2020
182020
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
142019
The landscape of chloroplast genome assembly tools
JA Freudenthal, S Pfaff, N Terhoeven, A Korte, MJ Ankenbrand, F Förster
bioRxiv 665869, 2019
82019
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
32022
Quantitative genetics from genome assemblies to neural network aided omics-based prediction of complex traits
JA Freudenthal
PQDT-Global, 2020
12020
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Articles 1–8