Jan Krumsiek
Jan Krumsiek
Weill Cornell Medicine
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Cited by
Cited by
An atlas of genetic influences on human blood metabolites
SY Shin, EB Fauman, AK Petersen, J Krumsiek, R Santos, J Huang, ...
Nature genetics 46 (6), 543-550, 2014
Genome-wide association analyses identify 18 new loci associated with serum urate concentrations
A Köttgen, E Albrecht, A Teumer, V Vitart, J Krumsiek, C Hundertmark, ...
Nature genetics 45 (2), 145-154, 2013
Gepard: a rapid and sensitive tool for creating dotplots on genome scale
J Krumsiek, R Arnold, T Rattei
Bioinformatics 23 (8), 1026-1028, 2007
Discovery of sexual dimorphisms in metabolic and genetic biomarkers
K Mittelstrass, JS Ried, Z Yu, J Krumsiek, C Gieger, C Prehn, ...
PLoS genetics 7 (8), e1002215, 2011
Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data
J Krumsiek, K Suhre, T Illig, J Adamski, FJ Theis
BMC systems biology 5 (1), 1-16, 2011
The dynamic range of the human metabolome revealed by challenges
S Krug, G Kastenmüller, F Stückler, MJ Rist, T Skurk, M Sailer, J Raffler, ...
The FASEB Journal 26 (6), 2607-2619, 2012
Statistical methods for the analysis of high-throughput metabolomics data
J Bartel, J Krumsiek, FJ Theis
Computational and structural biotechnology journal 4 (5), e201301009, 2013
Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling
DM Wittmann, J Krumsiek, J Saez-Rodriguez, DA Lauffenburger, S Klamt, ...
BMC systems biology 3 (1), 1-21, 2009
Gender-specific pathway differences in the human serum metabolome
J Krumsiek, K Mittelstrass, KT Do, F Stückler, J Ried, J Adamski, A Peters, ...
Metabolomics 11 (6), 1815-1833, 2015
Mining the unknown: a systems approach to metabolite identification combining genetic and metabolic information
J Krumsiek, K Suhre, AM Evans, MW Mitchell, RP Mohney, MV Milburn, ...
Public Library of Science 8 (10), e1003005, 2012
Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network
J Krumsiek, C Marr, T Schroeder, FJ Theis
PloS one 6 (8), e22649, 2011
Software tools for single-cell tracking and quantification of cellular and molecular properties
O Hilsenbeck, M Schwarzfischer, S Skylaki, B Schauberger, PS Hoppe, ...
Nature biotechnology 34 (7), 703-706, 2016
A metabolome-wide association study of kidney function and disease in the general population
P Sekula, ON Goek, L Quaye, C Barrios, AS Levey, W Römisch-Margl, ...
Journal of the American Society of Nephrology 27 (4), 1175-1188, 2016
Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects
D Lutter, C Marr, J Krumsiek, EW Lang, FJ Theis
BMC genomics 11 (1), 1-11, 2010
The gut microbiota promotes hepatic fatty acid desaturation and elongation in mice
A Kindt, G Liebisch, T Clavel, D Haller, G Hörmannsperger, H Yoon, ...
Nature communications 9 (1), 1-15, 2018
Odefy-from discrete to continuous models
J Krumsiek, S Pölsterl, DM Wittmann, FJ Theis
BMC bioinformatics 11 (1), 1-10, 2010
Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes
C Winkler, J Krumsiek, F Buettner, C Angermüller, EZ Giannopoulou, ...
Diabetologia 57 (12), 2521-2529, 2014
Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies
KT Do, S Wahl, J Raffler, S Molnos, M Laimighofer, J Adamski, K Suhre, ...
Metabolomics 14 (10), 1-18, 2018
Body fat free mass is associated with the serum metabolite profile in a population-based study
C Jourdan, AK Petersen, C Gieger, A Döring, T Illig, R Wang-Sattler, ...
PloS one 7 (6), e40009, 2012
Linking diet, physical activity, cardiorespiratory fitness and obesity to serum metabolite networks: findings from a population-based study
A Floegel, A Wientzek, U Bachlechner, S Jacobs, D Drogan, C Prehn, ...
International journal of obesity 38 (11), 1388-1396, 2014
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