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Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study.

Scientific data

Cai L, Wheeler E, Kerrison ND, Luan J, Deloukas P, Franks PW, Amiano P, Ardanaz E, Bonet C, Fagherazzi G, Groop LC, Kaaks R, Huerta JM, Masala G, Nilsson PM, Overvad K, Pala V, Panico S, Rodriguez-Barranco M, Rolandsson O, Sacerdote C, Schulze MB, Spijkerman AMW, Tjonneland A, Tumino R, van der Schouw YT, Sharp SJ, Forouhi NG, Riboli E, McCarthy MI, Barroso I, Langenberg C, Wareham NJ.
PMID: 33188205
Sci Data. 2020 Nov 13;7(1):393. doi: 10.1038/s41597-020-00716-7.

Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct...

Cite
Cai L, Wheeler E, Kerrison ND, et al. Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study. Sci Data. 2020;7(1):393doi: 10.1038/s41597-020-00716-7.
Cai, L., Wheeler, E., Kerrison, N. D., Luan, J., Deloukas, P., Franks, P. W., Amiano, P., Ardanaz, E., Bonet, C., Fagherazzi, G., Groop, L. C., Kaaks, R., Huerta, J. M., Masala, G., Nilsson, P. M., Overvad, K., Pala, V., Panico, S., Rodriguez-Barranco, M., Rolandsson, O., Sacerdote, C., Schulze, M. B., Spijkerman, A. M. W., Tjonneland, A., Tumino, R., van der Schouw, Y. T., Sharp, S. J., Forouhi, N. G., Riboli, E., McCarthy, M. I., Barroso, I., Langenberg, C., & Wareham, N. J. (2020). Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study. Scientific data, 7(1), 393. https://doi.org/10.1038/s41597-020-00716-7
Cai, Lina, et al. "Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study." Scientific data vol. 7,1 (2020): 393. doi: https://doi.org/10.1038/s41597-020-00716-7
Cai L, Wheeler E, Kerrison ND, Luan J, Deloukas P, Franks PW, Amiano P, Ardanaz E, Bonet C, Fagherazzi G, Groop LC, Kaaks R, Huerta JM, Masala G, Nilsson PM, Overvad K, Pala V, Panico S, Rodriguez-Barranco M, Rolandsson O, Sacerdote C, Schulze MB, Spijkerman AMW, Tjonneland A, Tumino R, van der Schouw YT, Sharp SJ, Forouhi NG, Riboli E, McCarthy MI, Barroso I, Langenberg C, Wareham NJ. Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study. Sci Data. 2020 Nov 13;7(1):393. doi: 10.1038/s41597-020-00716-7. PMID: 33188205; PMCID: PMC7666191.
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SCSPOD14, a South China Sea physical oceanographic dataset derived from in situ measurements during 1919-2014.

Scientific data

Zeng L, Wang D, Chen J, Wang W, Chen R.
PMID: 27116565
Sci Data. 2016 Apr 26;3:160029. doi: 10.1038/sdata.2016.29.

In addition to the oceanographic data available for the South China Sea (SCS) from the World Ocean Database (WOD) and Array for Real-time Geostrophic Oceanography (Argo) floats, a suite of observations has been made by the South China Sea...

Cite
Zeng L, Wang D, Chen J, et al. SCSPOD14, a South China Sea physical oceanographic dataset derived from in situ measurements during 1919-2014. Sci Data. 2016;3:160029doi: 10.1038/sdata.2016.29.
Zeng, L., Wang, D., Chen, J., Wang, W., & Chen, R. (2016). SCSPOD14, a South China Sea physical oceanographic dataset derived from in situ measurements during 1919-2014. Scientific data, 3160029. https://doi.org/10.1038/sdata.2016.29
Zeng, Lili, et al. "SCSPOD14, a South China Sea physical oceanographic dataset derived from in situ measurements during 1919-2014." Scientific data vol. 3 (2016): 160029. doi: https://doi.org/10.1038/sdata.2016.29
Zeng L, Wang D, Chen J, Wang W, Chen R. SCSPOD14, a South China Sea physical oceanographic dataset derived from in situ measurements during 1919-2014. Sci Data. 2016 Apr 26;3:160029. doi: 10.1038/sdata.2016.29. PMID: 27116565; PMCID: PMC4845715.
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Showing 49 to 50 of 50 entries