An analysis-ready and quality controlled resource for pediatric brain white-matter research

Autor: Richie-Halford, A., Cieslak, M., Ai, L., Caffarra, S., Covitz, S., Franco, A., Karipidis, I., Kruper, J., Milham, M., Avelar-Pereira, B., Roy, E., Sydnor, V., Yeatman, J., Abbott, N., Anderson, J., Gagana, B., Bleile, M., Bloomfield, P., Bottom, V., Bourque, J., Boyle, R., Brynildsen, J., Calarco, N., Castrellon, J., Chaku, N., Chen, B., Chopra, S., Coffey, E., Colenbier, N., Cox, D., Crippen, J., Crouse, J., David, S., Leener, B., Delap, G., Deng, Z., Dugre, J., Eklund, A., Ellis, K., Ered, A., Farmer, H., Faskowitz, J., Finch, J., Flandin, G., Flounders, M., Fonville, L., Frandsen, S., Garic, D., Garrido-Vásquez, P., Gonzalez-Escamilla, G., Grogans, S., Grotheer, M., Gruskin, D., Guberman, G., Haggerty, E., Hahn, Y., Hall, E., Hanson, J., Harel, Y., Vieira, B., Hettwer, M., Hobday, H., Horien, C., Huang, F., Huque, Z., James, A., Kahhale, I., Kamhout, S., Keller, A., Khera, H., Kiar, G., Kirk, P., Kohl, S., Korenic, S., Korponay, C., Kozlowski, A., Kraljevic, N., Lazari, A., Leavitt, M., Li, Z., Liberati, G., Lorenc, E., Lossin, A., Lotter, L., Lydon-Staley, D., Madan, C., Magielse, N., Marusak, H., Mayor, J., McGowan, A., Mehta, K., Meisler, S., Michael, C., Mitchell, M., Morand-Beaulieu, S., Newman, B., Nielsen, J., O’Mara, S., Ojha, A., Omary, A., Özarslan, E., Parkes, L., Peterson, M., Pines, A., Pisanu, C., Rich, R., Sahoo, A., Samara, A., Sayed, F., Schneider, J., Shaffer, L., Shatalina, E., Sims, S., Sinclair, S., Song, J., Hogrogian, G., Tooley, U., Tripathi, V., Turker, H., Valk, S., https://orcid.org/0000-0003-2998-6849, Wall, M., Walther, C., Wang, Y., Wegmann, B., Welton, T., Wiesman, A., Wiesman, M., Winters, D., Yuan, R., Zacharek, S., Zajner, C., Zakharov, I., Zammarchi, G., Zhou, D., Zimmerman, B., Zoner, K., Satterthwaite, T., Rokem, A.

Publikováno v: Scientific Data
Scientific Data, 9 (1)

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26d533a99e2a3d79a42501a0f25011a1
https://hdl.handle.net/21.11116/0000-000B-63EB-D21.11116/0000-000B-63ED-B

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Multi-Site Meta-Analysis of Morphometry

Autor: Jahanshad, N, Faskowitz, J, Roshchupkin, Gennady, Hibar, DP, Gutman, B A, Tustison, NJ, Adams, Hieab, Niessen, Wiro, Vernooij, Meike, Ikram, Arfan, Zwiers, MP, Vasquez, AA, Franke, B, Kroll, JL, Mwangi, B, Soares, JC, Ing, A, Desrivieres, S, Schumann, G, Hansell, NK, de Zubicaray, GI, McMahon, KL, Martin, NG, Wright, MJ, Thompson, PM, Alzheimer's Dis Neuroimaging, I

Publikováno v: IEEE-ACM Transactions on Computational Biology and Bioinformatics, 16(5), 1508-1514. Institute of Electrical and Electronics Engineers Inc.
Ieee/ACM Transactions on Computational Biology and Bioinformatics, 16, 5, pp. 1508-1514
IEEE/ACM Trans Comput Biol Bioinform
Ieee/ACM Transactions on Computational Biology and Bioinformatics, 16, 1508-1514

Genome-wide association studies (GWAS) link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are ne

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8583a542130d4365886d16b32acb3cb5
https://doi.org/10.1109/tcbb.2019.2914905

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