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  • Witt, H., Sahin-Toth, M., Landt, O., Chen, J. M., Kahne, T., Drenth, J. P., Kukor, Z., Szepessy, E., Halangk, W., Dahm, S., Rohde, K., Schulz, H. U., Le Marechal, C., Akar, N., Ammann, R. W., Truninger, K., Bargetzi, M., Bhatia, E., Castellani, C., Cavestro, G. M., Cerny, M., Destro-Bisol, G., Spedini, G., Eiberg, H., Jansen, J. B., Koudova, M., Rausova, E., Macek, M., Malats, N., Real, F. X., Menzel, H. J., Moral, P., Galavotti, R., Pignatti, P. F., Rickards, O., Spicak, J., Zarnescu, N. O., Bock, W., Gress, T. M., Friess, H., Ockenga, J., Schmidt, H., Pfutzer, R., Lohr, M., Simon, P., Weiss, F. U., Lerch, M. M., Teich, N., Keim, V., Berg, T., Wiedenmann, B., Luck, W., Groneberg, D. A., Becker, M., Keil, T., Kage, A., Bernardova, J., Braun, M., Guldner, C., Halangk, J., Rosendahl, J., Witt, U., Treiber, M., Nickel, R., Ferec, C.. A degradation-sensitive anionic trypsinogen (PRSS2) variant protects against chronic pancreatitis. Nat.Genet. 2006; 38 (6): 668-673
  • Gonzalez, J. R., Rodriguez-Santiago, B., Caceres, A., Pique-Regi, R., Rothman, N., Chanock, S. J., Armengol, L., Perez-Jurado, L. A.. A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data. BMC.Bioinformatics. 2011; 12 (1): 166
  • Esnaola, M., Puig, P., Gonzalez, D., Castelo, R., Gonzalez, J. R.. A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments. BMC.Bioinformatics. 2013; 14 (1): 254
  • Basagana, X., Barrera-Gomez, J., Benet, M., Anto, J. M., Garcia-Aymerich, J.. A Framework for Multiple Imputation in Cluster Analysis. Am.J.Epidemiol. 2013
  • Bradfield, J. P., Taal, H. R., Timpson, N. J., Scherag, A., Lecoeur, C., Warrington, N. M., Hypponen, E., Holst, C., Valcarcel, B., Thiering, E., Salem, R. M., Schumacher, F. R., Cousminer, D. L., Sleiman, P. M., Zhao, J., Berkowitz, R. I., Vimaleswaran, K. S., Jarick, I., Pennell, C. E., Evans, D. M., St Pourcain, B., Berry, D. J., Mook-Kanamori, D. O., Hofman, A., Rivadeneira, F., Uitterlinden, A. G., van Duijn, C. M., van der Valk, R. J., De Jongste, J. C., Postma, D. S., Boomsma, D. I., Gauderman, W. J., Hassanein, M. T., Lindgren, C. M., Magi, R., Boreham, C. A., Neville, C. E., Moreno, L. A., Elliott, P., Pouta, A., Hartikainen, A. L., Li, M., Raitakari, O., Lehtimaki, T., Eriksson, J. G., Palotie, A., Dallongeville, J., Das, S., Deloukas, P., McMahon, G., Ring, S. M., Kemp, J. P., Buxton, J. L., Blakemore, A. I., Bustamante, M., Guxens, M., Hirschhorn, J. N., Gillman, M. W., Kreiner-Moller, E., Bisgaard, H., Gilliland, F. D., Heinrich, J., Wheeler, E., Barroso, I., O'Rahilly, S., Meirhaeghe, A., Sorensen, T. I., Power, C., Palmer, L. J., Hinney, A., Widen, E., Farooqi, I. S., McCarthy, M. I., Froguel, P., Meyre, D., Hebebrand, J., Jarvelin, M. R., Jaddoe, V. W., Smith, G. D., Hakonarson, H., Grant, S. F.. A genome-wide association meta-analysis identifies new childhood obesity loci. Nat.Genet. 2012
  • Garcia-Closas, M., Ye, Y., Rothman, N., Figueroa, J. D., Malats, N., Dinney, C. P., Chatterjee, N., Prokunina-Olsson, L., Wang, Z., Lin, J., Real, F. X., Jacobs, K. B., Baris, D., Thun, M., De, Vivo I., Albanes, D., Purdue, M. P., Kogevinas, M., Kamat, A. M., Lerner, S. P., Grossman, H. B., Gu, J., Pu, X., Hutchinson, A., Fu, Y. P., Burdett, L., Yeager, M., Tang, W., Tardon, A., Serra, C., Carrato, A., Garcia-Closas, R., Lloreta, J., Johnson, A., Schwenn, M., Karagas, M. R., Schned, A., Andriole, G., Jr., Grubb, R., III, Black, A., Jacobs, E. J., Diver, W. R., Gapstur, S. M., Weinstein, S. J., Virtamo, J., Hunter, D. J., Caporaso, N., Landi, M. T., Fraumeni, J. F., Jr., Silverman, D. T., Chanock, S. J., Wu, X.. A genome-wide association study of bladder cancer identifies a new susceptibility locus within SLC14A1, a urea transporter gene on chromosome 18q12.3. Hum.Mol.Genet. 2011; 20 (21): 4282-9
  • Ramasamy, A., Curjuric, I., Coin, L. J., Kumar, A., McArdle, W. L., Imboden, M., Leynaert, B., Kogevinas, M., Schmid-Grendelmeier, P., Pekkanen, J., Wjst, M., Bircher, A. J., Sovio, U., Rochat, T., Hartikainen, A. L., Balding, D. J., Jarvelin, M. R., Probst-Hensch, N., Strachan, D. P., Jarvis, D. L.. A genome-wide meta-analysis of genetic variants associated with allergic rhinitis and grass sensitization and their interaction with birth order. J.Allergy Clin.Immunol. 2011; 128 (5): 996-1005
  • Thurston, G. D., Kipen, H., Annesi-Maesano, I., Balmes, J., Brook, R. D., Cromar, K., De Matteis, S., Forastiere, F., Forsberg, B., Frampton, M. W., Grigg, J., Heederik, D., Kelly, F. J., Kuenzli, N., Laumbach, R., Peters, A., Rajagopalan, S. T., Rich, D., Ritz, B., Samet, J. M., Sandstrom, T., Sigsgaard, T., Sunyer, J., Brunekreef, B.. A joint ERS/ATS policy statement: what constitutes an adverse health effect of air pollution? An analytical framework. Eur Respir.J 2017; 49 (1)
  • Moore, D. K., Jerrett, M., Mack, W. J., Kunzli, N.. A land use regression model for predicting ambient fine particulate matter across Los Angeles, CA. J Environ Monit. 2007; 9 (3): 246-252
  • Akita, Y., Baldasano, J. M., Beelen, R., Cirach, M., de Hoogh, K., Hoek, G., Nieuwenhuijsen, M. J., Serre, M. L., de Nazelle, A.. A large scale air pollution estimation method combining Land Use Regression and Chemical Transport Modeling in a geostatistical framework. Environ.Sci.Technol. 2014; 48 (8): 4452-9

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