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Torsten Pook
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Improving imputation quality in BEAGLE for crop and livestock data
T Pook, M Mayer, J Geibel, S Weigend, D Cavero, CC Schoen, ...
G3: Genes, Genomes, Genetics 10 (1), 177-188, 2020
582020
How array design creates SNP ascertainment bias
J Geibel, C Reimer, S Weigend, A Weigend, T Pook, H Simianer
PloS one 16 (3), e0245178, 2021
502021
MoBPS-modular breeding program simulator
T Pook, M Schlather, H Simianer
G3: Genes, Genomes, Genetics 10 (6), 1915-1918, 2020
472020
HaploBlocker: creation of subgroup-specific haplotype blocks and libraries
T Pook, M Schlather, G de Los Campos, M Mayer, CC Schoen, ...
Genetics 212 (4), 1045-1061, 2019
422019
Using local convolutional neural networks for genomic prediction
T Pook, J Freudenthal, A Korte, H Simianer
Frontiers in genetics 11, 561497, 2020
302020
Newly developed MAGIC population allows identification of strong associations and candidate genes for anthocyanin pigmentation in eggplant
G Mangino, A Arrones, M Plazas, T Pook, J Prohens, P Gramazio, ...
Frontiers in Plant Science 13, 847789, 2022
232022
A unifying concept of animal breeding programmes
H Simianer, L Büttgen, A Ganesan, NT Ha, T Pook
Journal of Animal Breeding and Genetics 138 (2), 137-150, 2021
152021
How imputation can mitigate SNP ascertainment Bias
J Geibel, C Reimer, T Pook, S Weigend, A Weigend, H Simianer
BMC genomics 22 (1), 340, 2021
132021
Accounting for epistasis improves genomic prediction of phenotypes with univariate and bivariate models across environments
E Vojgani, T Pook, JWR Martini, AC Hölker, M Mayer, CC Schön, ...
Theoretical and Applied Genetics 134, 2913-2930, 2021
102021
Simulation study on the integration of health traits in horse breeding programs
L Büttgen, J Geibel, H Simianer, T Pook
Animals 10 (7), 1153, 2020
102020
Turning the PAGE – the potential of genome editing in breeding for complex traits revisited
H Simianer, T Pook, M Schlather
Proc. 11th World Congress on Genetics Applied to Livestock Production …, 2018
92018
Increasing calling accuracy, coverage, and read-depth in sequence data by the use of haplotype blocks
T Pook, A Nemri, EG Gonzalez Segovia, D Valle Torres, H Simianer, ...
PLoS Genetics 17 (12), e1009944, 2021
62021
The Modular Breeding Program Simulator (MoBPS) allows efficient simulation of complex breeding programs
T Pook, C Reimer, A Freudenberg, L Büttgen, J Geibel, A Ganesan, ...
Animal Production Science, 2021
52021
MoBPSweb: A web-based framework to simulate and compare breeding programs
T Pook, L Büttgen, A Ganesan, NT Ha, H Simianer
G3 11 (2), jkab023, 2021
52021
Genomic prediction using information across years with epistatic models and dimension reduction via haplotype blocks
E Vojgani, AC Hölker, M Mayer, CC Schön, H Simianer, T Pook
PLoS one 18 (3), e0282288, 2023
42023
Development and validation of a horse reference panel for genotype imputation
P Reich, C Falker-Gieske, T Pook, J Tetens
Genetics Selection Evolution 54 (1), 49, 2022
42022
Phenotype Prediction under Epistasis
E Vojgani, T Pook, H Simianer
Epistasis: Methods and Protocols, 105-120, 2021
42021
Accelerated matrix-vector multiplications for matrices involving genotype covariates with applications in genomic prediction
A Freudenberg, J Vandenplas, M Schlather, T Pook, R Evans, ...
Frontiers in Genetics 14, 1220408, 2023
32023
Imputation of low‐density marker chip data in plant breeding: Evaluation of methods based on sugar beet
T Niehoff, T Pook, M Gholami, T Beissinger
The Plant Genome 15 (4), e20257, 2022
32022
How Array Design Affects SNP Ascertainment Bias
J Geibel, C Reimer, S Weigend, A Weigend, T Pook, H Simianer
bioRxiv, 833541, 2019
32019
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