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Sebastian J. Schultheiss
Sebastian J. Schultheiss
computomics.com
Verifisert e-postadresse på computomics.com - Startside
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Multiple reference genomes and transcriptomes for Arabidopsis thaliana
X Gan, O Stegle, J Behr, JG Steffen, P Drewe, KL Hildebrand, R Lyngsoe, ...
Nature 477 (7365), 419-423, 2011
7702011
Hormonal control of the shoot stem-cell niche
Z Zhao, SU Andersen, K Ljung, K Dolezal, A Miotk, SJ Schultheiss, ...
Nature 465 (7301), 1089-1092, 2010
5642010
De novo assembly of the cattle reference genome with single-molecule sequencing
BD Rosen, DM Bickhart, RD Schnabel, S Koren, CG Elsik, E Tseng, ...
Gigascience 9 (3), giaa021, 2020
5282020
Transcriptional control of a plant stem cell niche
W Busch, A Miotk, FD Ariel, Z Zhao, J Forner, G Daum, T Suzaki, ...
Developmental cell 18 (5), 841-853, 2010
2432010
Accurate machine learning-based germination detection, prediction and quality assessment of three grain crops
N Genze, R Bharti, M Grieb, SJ Schultheiss, DG Grimm
Plant methods 16, 1-11, 2020
752020
Modernizing the bovine reference genome assembly
BD Rosen, DM Bickhart, RD Schnabel, S Koren, CG Elsik, A Zimin, ...
Proceedings of the 11th world congress on genetics applied to livestock …, 2018
552018
De novo assembly of the cattle reference genome with singlemolecule sequencing. Gigascience 9: giaa021
BD Rosen, DM Bickhart, RD Schnabel, S Koren, CG Elsik, E Tseng, ...
422020
KIRMES: kernel-based identification of regulatory modules in euchromatic sequences
SJ Schultheiss, W Busch, JU Lohmann, O Kohlbacher, G Rätsch
Bioinformatics 25 (16), 2126-2133, 2009
402009
KIRMES: kernel-based identification of regulatory modules in euchromatic sequences
S Schultheiss, W Busch, J Lohmann, O Kohlbacher, G Rätsch
BMC Bioinformatics 10 (Suppl 13), O1, 2009
402009
Persistence and availability of Web services in computational biology
SJ Schultheiss, MC Münch, GD Andreeva, G Rätsch
PloS one 6 (9), e24914, 2011
392011
A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species
M John, F Haselbeck, R Dass, C Malisi, P Ricca, C Dreischer, ...
Frontiers in Plant Science 13, 932512, 2022
262022
Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis
VT Sreedharan, SJ Schultheiss, G Jean, A Kahles, R Bohnert, P Drewe, ...
Bioinformatics 30 (9), 1300-1301, 2014
192014
MethylScore, a pipeline for accurate and context-aware identification of differentially methylated regions from population-scale plant whole-genome bisulfite sequencing data
P Hüther, J Hagmann, A Nunn, I Kakoulidou, R Pisupati, D Langenberger, ...
Quantitative Plant Biology 3, e19, 2022
182022
Ten simple rules for providing a scientific web resource
SJ Schultheiss
PLoS Computational Biology 7 (5), e1001126, 2011
182011
Oqtans: a Galaxy-integrated workflow for quantitative transcriptome analysis from NGS Data
SJ Schultheiss, G Jean, J Behr, R Bohnert, P Drewe, N Görnitz, A Kahles, ...
BMC Bioinformatics 12, 1-2, 2011
62011
Kernel-based identification of regulatory modules
SJ Schultheiss
Computational Biology of Transcription Factor Binding, 213-223, 2010
52010
Approaches taken, progress made, and enhanced utility of long read-based goat, swine, cattle and sheep reference genomes
TPL Smith, S Koren, A Phillippy, DM Bickhart, BD Rosen, KC Worley, ...
Plant and Animal Genome XXIV, 2016
32016
Learn from the Best
V Bernard, SJ Schultheiss, M Michaut
PLoS computational biology 10 (5), e1003645, 2014
32014
Interpretable machine learning decodes soil microbiome’s response to drought stress
M Hagen, R Dass, C Westhues, J Blom, SJ Schultheiss, S Patz
Environmental Microbiome 19 (1), 35, 2024
22024
Crowd-Sourcing Design: Sketch Minimization using Crowds for Feedback.
D Engel, V Kottler, C Malisi, M Roettig, EM Willing, S Schultheiss
HCOMP@ AAAI, 2012
22012
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Artikler 1–20