Can data repositories help find effective treatments for complex diseases?

Progress in Neurobiology

Volumn 152, Issue , 2017, Pages 200-212

  Farber, Gregory K ^a  

^a NATIONAL INSTITUTE OF MENTAL HEALTH   (United States)

Author keywords

Common data elements; Consents; Data infrastructure; Data repositories; Data sharing; Imaging data

Indexed keywords

CLINICAL DATA REPOSITORY; COMMON DATA ELEMENTS; DISEASES; GENBANK; GENE EXPRESSION; HUMAN; INFORMATION PROCESSING; NEUROIMAGING; ORGANIZATION AND MANAGEMENT; PRIORITY JOURNAL; REVIEW; DATABASE MANAGEMENT SYSTEM; FACTUAL DATABASE; HEALTH SURVEY; INFORMATION RETRIEVAL; PROCEDURES; REGISTER;

DATABASE MANAGEMENT SYSTEMS; DATABASES, FACTUAL; DATASETS AS TOPIC; DISEASE; HUMANS; INFORMATION STORAGE AND RETRIEVAL; POPULATION SURVEILLANCE; REGISTRIES;

EID: 84963595317     PISSN: 03010082     EISSN: 18735118     Source Type: Journal    
DOI: 10.1016/j.pneurobio.2016.03.008     Document Type: Review

References (82)

1. Aguirre, G.K., FIASCO, VoxBo, and MEDx: behind the code. Neuroimage 62:2 (2012), 765–767.
2. Barrett, T., Edgar, R., Gene expression omnibus (GEO) microarray data storage, submission, retrieval, and analysis. Methods Enzymol. 411 (2006), 352–369.
3. Barrett, T., Wilhite, S.E., Ledoux, P., Evangelista, C., Kim, I.F., Tomashevsky, M., Marshall, K.A., Phillippy, K.H., Sherman, P.M., Holko, M., Yefanov, A., Lee, H., Zhang, N., Robertson, C.L., Serova, N., Davis, S., Soboleva, A., NCBI GEO: archive for functional genomics data sets −Update. Nucleic Acids Res. 41:Database Issue (2013), D991–D995.
4. Beberg, A.L., Ensign, D.L., Jayachandran, G., Khaliq, S., Pande, V.S., Folding@home: Lessons from eight Years of Volunteer Distributed Computing, Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on, 2009, 1–8.
5. Benson, D.A., Clark, K., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J., Saysers, E.W., GenBank. Nucleic Acids Res. 43:Database issue (2015), D30–D35.
6. Berman, H.M., The protein data bank: a historical perspective. Acta Cryst. Sect. A A64 (2008), 88–95.
7. Biswal, B.B., Mennes, M., Zuo, X.N., Gohel, S., Kelly, C., Smith, S.M., Beckmann, C.F., Adelstein, J.S., Buckner, R.L., Colcombe, S., Dogonowski, A.M., Ernst, M., Fair, D., Hampson, M., Hoptman, M.J., Hyde, J.S., Kiviniemi, V.J., Kotter, R., Li, S.J., Lin, C.P., Lowe, M.J., Mackay, C., Madden, D.J., Madsen, K.H., Margulies, D.S., Mayberg, H.S., McMahon, K., Monk, C.S., Mostofsky, S.H., Nagel, B.J., Pekar, J.J., Peltier, S.J., Petersen, S.E., Riedl, V., Rombouts, S.A., Rypma, B., Schlaggar, B.L., Schmidt, S., Seidler, R.D., Siegle, G.J., Sorg, C., Teng, G.J., Veijola, J., Villringer, A., Walter, M., Wang, L., Weng, X.C., Whitfield-Gabrieli, S., Williamson, P., Windischberger, C., Zang, Y.F., Zhang, H.Y., Castellanos, F.X., Milham, M.P., Toward discovery science of human brain function. Proc. Natl. Acad. Sci. U. S. A. 107 (2010), 4734–4739.
8. Brunger, A.T., Free r value: a novel statistical quantity for assessing the accuracy of crystal structures. Nature 355:6359 (1992), 472–475.
9. Buhrmester, M., Kwang, T., Gosling, S.D., Amazon's mechanical turk: a new source of inexpensive yet high-quality data? perspect. Psychol. Sci. 6:1 (2011), 3–5.
10. Cheung, K.-H., Prudhommeaux, E., Wang, Y., Stephens, S., Semantic web for health care and life sciences: a review of the state of the art. Brief. Bioinform. 10:2 (2009), 111–113.
11. Collins, F.S., Tabak, L.A., Policy: NIH plans to enhance reproducibility. Nature 505:7485 (2014), 612–613.
12. Collins, F.S., Patrinos, A., Jordan, E., Chakravarti, A., gesteland, R., Walters, L., New goals for the U.S. human genome project: 1998–2003. Science 282:5389 (1998), 682–689.
13. Conway, K.P., Vullo, G.C., Kennedy, A.P., Finger, M.S., Agrawal, A., Bjork, J.M., Farrer, L.A., Hancock, D.B., Hussong, A., Wakim, P., Huggins, W., Hendershot, T., Nettles, D.S., Pratt, J., Maiese, D., Junkins, H.A., Ramos, E.M., Strader, L.C., Hamilton, C.M., Sher, K.J., Data compatibility in the addiction sciences: an examination of measure commonality. Drug Alcohol Depend. 141 (2014), 153–158.
14. Cooper, S., Khatib, F., Treuille, A., Barbero, J., Lee, J., Beenen, M., Leaver-Fay, A., Baker, D., Popovic, Z., FoldIt players, Predicting protein structures with a multiplayer online game. Nature 446 (2010), 756–760.
15. Curtis, L.H., Weiner, M.G., Boudreau, D.M., Cooper, W.O., Daniel, G.W., Nair, V.P., Raebel, M.A., Beaulieu, N.U., Rosofsky, R., Woodworth, T.S., Brown, J.S., Design considerations, architecture, and use of the mini-Sentinel distributed data system. Pharmacoepidemiol. Drug Saf. 21:Suppl. 1 (2012), 23–31.
16. DeMauro, A., Greco, M., Grimaldi, M., What is Big Data? A Consensual Definition and Review of Key Research Topics. 4th International Conference on Integrated Information, Madrid, 2014, 10.13140/2.1.2341.5048.
17. Edgar, R., Barrett, T., NCBI GEO standards and services for microarray data. Nat. Biotechnol. 24:12 (2006), 1471–1472.
18. Edgar, R., Domrachev, M., Lash, A.E., Gene expression omnibus: nCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30:1 (2002), 207–210.
19. Fitzgerald, P.M.D., Westbrook, J.D., Bourne, P.E., McMahon, B., Watenpaugh, K.D., Berman, H.M., International tables for crystallography. Hall, S.R., McMahon, B., (eds.) Definition and Exchange of Crystallographic Data, Ch. 4.5, Macromolecular Dictionary (mmCIF), Vol. G, 2005, Springer, Dordrecht, 295–443.
20. Foster, J.A., Neufield, K.A., Gut-Brian axis: how the microbiome influences anxiety and depression. Trends Neurosci. 36:5 (2013), 305–312.
21. Friedman, L., Glover, G.H., Report on a multicenter fMRI quality assurance protocol. J. Magn. Reson. Imaging 23:6 (2006), 827–839.
22. Friend, S.H., Norman, T.C., Metcalfe's law and the biology information commons. Nat. Biotechnol. 31 (2013), 297–303.
23. Gardner, D., Akil, H., Ascoli, G.A., Bowden, D.M., Bug, W., Donohue, D.E., Goldberg, D.H., Grafstein, B., Grethe, J.S., Gupta, A., Halavi, M., Kennedy, D.N., Marenco, L., Martone, M.E., Miller, P.L., Müller, H.M., Robert, A., Shepherd, G.M., Sternberg, P.W., Van Essen, D.C., Williams, R.W., The neuroscience information framework: a data and knowledge environment for neuroscience. Neuroinformatics 6:3 (2008), 149–160.
24. Geer, R.C., Sayers, E.W., Entrez: making use of its power. Brief. Bioinform. 4:2 (2003), 179–184.
25. Gershon, R.C., Rothrock, N.E., Hanrahan, R.T., Jansky, L.J., Harniss, M., Riley, W., The development of a clinical outcomes survey research application: assessment Center. Qual. Life Res. 19:5 (2010), 677–685.
26. Green, E.D., Watson, J.D., Collins, F.S., Twenty-five years of big biology. Nature 526:7571 (2015), 29–31.
27. Grinnon, S.T., Miller, K., Marler, J.R., Lu, Y., Stout, A., Odenkirchen, J., Kunitz, S., National institute of neurological disorders and stroke common data element project–approach and methods. Clin. Trials 9:2 (2012), 322–329.
28. Groom, C.R., Allen, F.H., The cambridge structural database in retrospect and prospect. Angew. Chem. Int. Ed. Engl. 53:3 (2014), 662–671.
29. Guggenberger, R., Nanz, D., Bussmann, L., Chhabra, A., Fischer, M.A., Hodler, J., Pfirrmann, C.W., Andreisek, G., Diffusion tensor imaging of the median nerve at 3.0T using different MR scanners: agreement of FA and ADC measurements. Eur. J. Ratiol. 82:10 (2013), e590–e596.
30. Gunter, J.L., Bernstein, M.A., Borowski, B.J., Ward, C.P., Britson, P.J., Felmlee, J.P., Schuff, N., Weiner, M., Jack, C.R., Measurement of MRI scanner performance with the ADNI phantom. Med. Phys. 36:6 (2009), 2193–2205.
31. Hall, D., Huerta, M.F., McAuliffe, M.J., Farber, G.K., Sharing heterogeneous data: the national database for autism research. Neuroinformation 10 (2012), 331–339.
32. Hamilton, C.M., Strader, L.C., Pratt, J.G., Maiese, D., Hendershot, T., Kwok, R.K., Hammond, J.A., Huggins, W., Jackman, D., Pan, H., Nettles, D.S., Beaty, T.H., Farrer, L.A., Kraft, P., Marazita, M.L., Ordovas, J.M., Pato, C.N., Spitz, M.R., Wagener, D., Williams, M., Junkins, H.A., Harlan, W.R., Ramos, E.M., Haines, J., The PhenX toolkit: get the most from your measures. Am. J. Epidemiol. 174:3 (2011), 253–260.
33. Hibar, D.P., et al. Common genetic variants influence human subcortical brain structures. Nature 520 (2015), 224–229.
34. Husser, C.S., Buchhalter, J.R., Raffo, O.S., Shabo, A., Brown, S.H., Lee, K.E., Elkin, P.L., Standardization of microarray and pharmacogenomics data. Methods Mol. Biol. 316 (2006), 111–157.
35. Jack, C.R. Jr., Bernstein, M.A., Fox, N.C., Thompson, P., Alexander, G., Harvey, D., Borowski, B., Britson, P.J., Whitwell, J., Ward, C., Dale, A.M., Felmlee, J.P., Gunter, J.L., Hill, D.L., Killany, R., Schuff, N., Fox-Bosetti, S., Lin, C., Studholme, C., DeCarli, C.S., Krueger, G., Ward, H.A., Netzger, G.J., Scott, K.T., Mallozzi, R., Blezek, D., Levy, J., Debbins, J.P., Fleisher, A.S., Albert, M., Green, R., Bartzokis, G., Glover, G., Mugler, J., Weiner, M.W., The alzehimer's disease neuroimaging initiative (ADNI): MRI methods. J. Magn. Reson. Imaging 27:4 (2008), 685–691.
36. Jagadish, H.V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J.M., Ramakrishnan, R., Shahabi, C., Big data and its technical challenges. Commun. ACM 57:7 (2014), 86–94.
37. Jahanshad, N., Kochunov, P.V., Sprooten, E., Mandl, R.C., Nichols, T.E., Almasy, L., Blangero, J., Brouwer, R.M., Curran, J.E., de Zubicaray, G.I., Duggirala, R., Fox, P.T., Hong, L.E., Landman, B.A., Martin, N.G., McMahon, K.L., Medland, S.E., Mitchell, B.D., Olvera, R.L., Peterson, C.P., Starr, J.M., Sussmann, J.E., Toga, A.W., Wardlaw, J.M., Wright, M.J., Hulshoff Pol, H.E., Bastin, M.E., McIntosh, A.M., Deary, I.J., Thompson, P.M., Glahn, D.C., Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group. Neuroimage 81 (2013), 455–469.
38. Johnson, S.B., Whitney, G., McAuliffe, M., Wang, H., McCreedy, E., Rozenblit, L., Evans, C.C., Using global unique identifiers to link autism collections. J. Am. Med. Inform. Assoc. 17 (2010), 689–695.
39. Jorgenson, L.A., Newsome, W.T., Anderson, D.J., Bargmann, C.I., Brown, E.N., Deisseroth, K., Donoghue, J.P., Hudson, K.L., Ling, G.S.F., MacLeish, P.R., Marder, E., Normann, R.A., Sanes, J.R., Schnitzer, M.J., Sejnowski, T.J., Tank, D.W., Tsien, R.Y., Ugurbil, K., Wingfield, J.C., The BRAIN initiative: developing technology to catalyse neuroscience discovery. Phil. Trans. R. Soc. B., 370, 2015, 20140164.
40. Kaye, J., Curren, L., Anderson, N., Edwards, K., Fullerton, S.M., Kanellopoulou, N., Lund, D., MacArthur, D.G., Mscalzoni, D., Shepherd, J., Taylor, P.L., Terry, S.F., Winter, S.F., From patients to partners: participant-Centric initiatives in biomedical research. Nat. Rev. Genet. 13:5 (2012), 371–376.
41. Kochunov, P., Jahanshad, N., Sprooten, E., Nichols, T.E., Mandl, R.C., Almasy, L., Booth, T., Brouwer, R.M., Curran, J.E., de Zubicaray, G.I., Dimitrova, R., Duggirala, R., Fox, P.T., Elliot Hong, L., Landman, B.A., Lemaitre, H., Lopez, L.M., Martin, N.G., McMahon, K.L., Mitchell, B.D., Olvera, R.L., Peterson, C.P., Starr, J.M., Sussmann, J.E., Toga, A.W., Wardlaw, J.M., Wright, M.J., Wright, S.N., Bastin, M.E., McIntosh, A.M., Boomsma, D.I., Kahn, R.S., den Braber, A., de Geus, E.J., Deary, I.J., Hulshoff Pol, H.E., Williamson, D.E., Blangero, J., van ‘t Ent, D., Thompson, P.M., Glahn, D.C., Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: comparing meta and megaanalytical approaches for data pooling. Neuroimage 95 (2014), 136–150.
42. Kodama, Y., Shumway, M., Leinonen, R., International Nucleotidy Sequence Database Collaboration, The sequence read archive: explosive growth of sequence data. Nucleic Acids Res. 40:Database issue (2012), D54–D56.
43. Komorowski, M., Hard Drive Cost Per Gigabyte. 2014 http://www.mkomo.com/cost-per-gigabyte-update.
44. Krumm, N., Turner, T.N., Baker, C., Vives, L., Mohajeri, K., Witherspoon, K., Raja, A., Coe, B.P., Stessman, H.A., He, Z.-X., Leal, S.M., Bernier, R., Eichler, E.E., Excess of rare, inherited truncating mutations in autism. Nat. Genet., 2015, 10.1038/ng.3303 (published online 11 May).
45. Lee, H., Marvin, A.R., Watson, T., Piggot, J., Law, J.K., Law, P.A., Constantino, J.N., Nelson, S.F., Accuracy of phenotyping of autistic children based on internet implemented parent report. Am. J. Met. Genet. B Neuropsychiatr. Genet. 0:6 (2010), 1119–1126.
46. Leung, L., How Much Data Does X Store?. 2014 http://techexpectations.org/2014/05/17/how-much-data-does-x-store/.
47. Levine, S.Z., Rabinowitz, J., Uher, R., Kapur, S., Biomarkers of treatment outcome in schizophrenia: defining a benchmark for clinical significance. Eur. Neuropsychopharmacol., 2015, 10.1016/j.euroneuro.2015.06.008 (Epub ahead of print).
48. Li, M., Luo, X.J., Rietschel, M., Lewis, C.M., Mattheisen, M., Müller-Myhsok, B., Jamain, S., Leboyer, M., Landén, M., Thompson, P.M., Cichon, S., Nöthen, M.M., Schulze, T.G., Sullivan, P.F., Bergen, S.E., Donohoe, G., Morris, D.W., Hargreaves, A., Gill, M., Corvin, A., Hultman, C., Toga, A.W., Shi, L., Lin, Q., Shi, H., Gan, L., Meyer-Lindenberg, A., Czamara, D., Henry, C., Etain, B., Bis, J.C., Ikram, M.A., Fornage, M., Debette, S., Launer, L.J., Seshadri, S., Erk, S., Walter, H., Heinz, A., Bellivier, F., Stein, J.L., Medland, S.E., Arias Vasquez, A., Hibar, D.P., Franke, B., Martin, N.G., Wright, M.J., MooDS Bipolar Consortium, Swedish Bipolar Study Group, Alzheimer's Disease Neuroimaging Initiative, ENIGMA Consortium, CHARGE Consortium, Su, B., Allelic differences between Europeans and Chinese for CREB1 SNPs and their implications in gene expression regulation, hippocampal structure and function, and bipolar disorder susceptibility. Mol. Psychiatry 19:4 (2014), 452–461.
49. Luo, X.Z., Kennedy, D.N., Cohen, Z., Neuroimaging informatics tools and resources clearinghouse (NITRC) resource announcement. Neuroinformatics 7:1 (2009), 55–56.
50. Marcus, D.S., Olsen, T.R., Ramaratnam, M., Buckner, R.L., The extensible neuroimaging archive toolkit (XNAT) an informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics 5 (2007), 11–34.
51. Margolis, R., Derr, L., Dunn, M., Huerta, M., Larkin, J., Sheehan, J., Guyer, M., Green, E.D., The national institutes of health's big data to knowledge (BD2K) initiative: capitalizing on biomedical big data. J. Am. Med. Inform. Assoc., 21, 2014, 957.
52. Masseroli, M., Mons, B., Bongcam-Rudloff, E., Ceri, S., Kel, A., Rechenmann, F., Lisack, F., Roman, P., Integrated bio-Search: challenges and trends for the integration search, and comprehensive processing of biological information. BMC Bioinf., 15(Suppl. 1), 2014, S2.
53. McCray, A.T., Trevvett, P., Frost, H.R., Modeling the autism spectrum disorder. Neuroinformatics 12:2 (2014), 291–305.
54. Mennes, M., Biswal, B.B., Castellanos, F.X., Milham, M.P., Making data sharing work: the FCP/INDI experience. Neuroimage 82 (2013), 683–691.
55. Min, H., Ohira, R., Collins, M.A., Bondy, J., Avis, N.E., Tchuvatkina, O., Courtney, P.K., Moser, R.P., Shaikh, A.R., Hesse, B.W., Cooper, M., Reeves, D., Lanese, B., Helba, C., Miller, S.M., Ross, E.A., Sharing behavioral data through a grid infrastructure using data standards. J. Am. Med. Inform. Assoc. 21:4 (2014), 642–649.
56. Paraiso-Medina, S., Perez-Rey, D., Bucur, A., Claerhout, B., Alonso-Calvo, R., Semantic normalization and query abstraction based on SNOMED-CT and HL7: supporting multicentric clinical trials. IEEE J. Biomed. Health Inform. 19:3 (2015), 1061–1067.
57. Piwowar, H.A., Who shares? who doesnt? factors associated with openly archiving raw research data. PLoS One, 6(7), 2011, e18657.
58. Poldrack, R.A., Barch, D.M., Mitchell, J.P., Wager, T.D., Wagner, A.D., Devlin, J.T., Cumba, C., Kpyejo, O., Milham, M.P., Toward open sharing of task-based fMRI data: the OpenfMRI project. Front Neuroinform. 7:12 (2013), 1–12.
59. Savage, C.J., Vickers, A.J., Empirical study of data sharing by authors publishing in PLoS journals. PLoS One, 4(9), 2009, e7078.
60. Schadt, E.E., Lindeman, M.D., Sorenson, J., Lee, L., Nolan, G.P., Computing solutions to large-Scale data management and analysis. Nat. Rev. Genet. 11 (2010), 647–657.
61. Scott, A., Courtney, W., Wood, D., de la Garza, R., Land, S., King, M., Wang, R., Roberts, J., Turner, J.A., Calhoun, V.D., COINS: an innovative informatics and neuroimaging tool suite built for large heterogeneous datasets. Front. Neuroinf. 5:33 (2011), 1–15.
62. Smith, S.M., Vidaurre, D., Beckmann, C.F., Glasser, M.F., Jenkinson, M., Miller, K.L., Nichols, T.E., Robinson, E.C., Salimi-Khorshidi, G., Woolrich, M.W., Barch, D.M., Ugurbil, K., Van Essen, D.C., Functional connectomics from resting-State fMRI. Trends Cogn. Sci. 17:12 (2013), 666–680.
63. Smith, T.F., The History of Genetic Sequence Databases 6 (1990), 701–707.
64. Stein, J.L., et al. Identification of common variants associated with human hippocampal and intracranial volumes. Nat. Genet. 44:5 (2012), 552–561.
65. Stephens, Z.D., Lee, S.Y., Faghri, f., Campbell, r.H., Zhai, C., Efron, M.J., Iyer, R., Schatz, M.C., Sinha, S., Robinson, G.E., Big data: astronomical or genomical?. PLoS Biol., 13(7), 2015, e1002195.
66. Strasser, B.J., GenBank–Natural history in the 21st century. Science 322:5901 (2008), 537–538.
67. Strasser, B.J., Collecting, comparing, and computing sequences: the making of margaret O. dayhoff's atlas of Protein–1965. J. Hist. Biol. 43:4 (2010), 623–660.
68. Suber, P., An open access mandate for the national institutes of health. Open Med. 2:2 (2008), e39–e41.
69. Teeters, J.L., Harris, K.D., Milman, J., Olshausen, B.A., Sommer, F.T., Data sharing for computational neuroscience. Neuroinformatics 6:1 (2008), 47–55.
70. The Governing Council of the Organization for human brain mapping, Neuroimaging databases. Science 292 (2001), 1672–1676.
71. Thompson, P.M., et al. The ENIGMA consortium: large-scale collaborative analysis of neuroimaging and genetic data. Brain Imaging Behav. 8:2 (2014), 153–182.
72. Torgerson, C.M., Quinn, C., Dinov, I., Liu, Z., Petrosyan, P., Pelphrey, K., Haselgrove, C., Kennedy, D.N., Toga, A.W., Van Horn, J.D., Interacting with the national database for autism research (NDAR) via the LONI pipeline workflow environment. Brain Imaging Behav. 9 (2015), 89–103.
73. Tregarthen, J.P., Lock, J., Darcy, A.M., Development of a smartphone application for eating disorder self-Monitoring. Int. J. Eat. Disord. 48:7 (2015), 972–982.
74. Turner, J.A., Laird, A.R., The cognitive paradigm ontology: design and application. Neuroinformatics 10 (2012), 57–66.
75. Uher, R., Tansey, K.E., Malki, K., Perlis, R.H., Biomarkers predicting treatment outcome in depression: what is clinically significant?. Pharmacogenomics 13:2 (2012), 233–240.
76. Utturkar, S.M., Klingeman, D.M., Land, M.L., Schadt, C.W., Doktycz, M.J., Pelletier, D.A., Brown, S.D., Evaluation and validation of de novo and hybrid assembly techniques to derive high-quality genome sequences. Bioinformatics 30:19 (2014), 2709–2716.
77. Van Essen, D.C., Smith, S.M., Barch, D.M., Behrens, T.E.J., Yacoub, E., Ugurbil, K., for the WU-Minn HCP Consortium, The WU-Minn human connectome project: an overview. Neuroimage 80 (2013), 62–79.
78. Van Horn, J.D., Gazzaniga, M.S., Why share data?: lessons learned from the fMRIDC. Neuroimage 82 (2013), 677–682.
79. Van Horn, J.D., Toga, A.W., Is it time to Re-prioritize neuroimaging databases and digital repositories?. Neuroimage 47 (2009), 1720–1734.
80. VanBuecken, D.E., Greenbaum, C.J., Residual C-peptide in type 1 diabetes: what do we really know? pediatr. Diabetes 15:2 (2014), 84–90.
81. Walker, L., Curry, M., Nayak, A., Lange, N., Pierpaoli, C., Brain Development Cooperative Group, A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies. Hum. Brain Mapp. 34:10 (2013), 2439–2454.
82. Wicks, P., Massagli, M., Frost, J., Brownstein, C., Okun, S., Vaughan, T., Bradley, R., Heywood, J., Sharing health data for better outcomes on PatientsLikeMe. J. Med. Internet Res., 12(2), 2010, e19.