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Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans

Timmons, J A; Knudsen, S; Rankinen, T; Koch, L G; Sarzynski, M; Jensen, T; Keller, P; Scheele, C; Vollaard, N B J; Nielsen, S; Akerstrom, T; MacDougald, OA; Jansson, E; Greenhaff, P L; Tarnopolsky, M A; Van Loon, L J C; Pedersen, B K; Sundbert, C J; Wahlestedt, C; Britton, S L; Bouchard, C

Authors

J A Timmons

S Knudsen

T Rankinen

L G Koch

M Sarzynski

T Jensen

P Keller

C Scheele

N B J Vollaard

S Nielsen

T Akerstrom

OA MacDougald

E Jansson

P L Greenhaff

M A Tarnopolsky

L J C Van Loon

B K Pedersen

C J Sundbert

C Wahlestedt

S L Britton

C Bouchard



Citation

Timmons, J. A., Knudsen, S., Rankinen, T., Koch, L. G., Sarzynski, M., Jensen, T., …Bouchard, C. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. Journal of Applied Physiology, 108(6), 1487-1496. https://doi.org/10.1152/japplphysiol.01295.2009

Journal Article Type Article
Deposit Date Nov 11, 2014
Journal Journal of Applied Physiology
Print ISSN 8750-7587
Publisher American Physiological Society
Volume 108
Issue 6
Pages 1487-1496
DOI https://doi.org/10.1152/japplphysiol.01295.2009
Public URL https://rvc-repository.worktribe.com/output/1424122
Additional Information Corporate Creators : Copenhagen, Karolinska Inst, Sweden, Maastricht Uni Medical Centre, McMaster, Medical Prognosis Institute, Denmark, Michigan, Nottingham, Pennington Biomedical Research Centre, Scripps Research Inst, CA, USA, Stockholm University



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