Institut für Medizinische Statistik - UMG

Dr. Mohammed Dakna


Wissenschaftlicher Mitarbeiter - Zentrale Serviceeinheit Medizinische Biometrie und Statistische Bioinformatik
Telefon:
0551-39-12270
Telefax:
0551-39-4995
E-Mail:
Mohammed.Dakna@med.uni-goettingen.de
Ort:
Humboldtallee 32, EG 164
ORCID iD:
 orcid.org//0000-0001-8341-0360
Forschungsinteressen

  1. Analyze von Massenspectrometrischen Daten in der Proteomik- und Metabolomikforschung
  2. Medizinische Diagnose durch Kombinatin von klinischen Daten und neue hochdimensionale molekulare Biomarker
  3. Statistische Analyze von Daten mit fehlenden Werten
  4. Informationstheorie


Kurzer Lebenslauf

[Seit   2016] Wissenschaftlicher Mitarbeiter an der zentralen Serviceeinheit
Medizinische Biometrie und Statistische Bioinformatik , Göttingen
[2006 - 2016]Leiter der Biostatistik und Bioinformatik, Mosaiques-Diagnostics GmbH,
Hannover
[2004 - 2005] Fachlehrer für Physik und Mathematik in der Erwachsenen-Fortbildung, Göttingen
[1999 - 2004] Wissenschaftlicher Mitarbeiter am theoretisch-physikalischen Institut,
Göttingen
[1995 - 1999] Promotion und Wissenschaftlicher Mitarbeiter in der
Quanteninformationverarbbeitung, Jena
[Hier sind zwei Papers, die Teile meiner Doctor-Arbeit waren und mehr
als 100 Mal in den Zeitschriften der APS (American Physical Society)
zitiert sind Paper1 und Paper2 ]
[1992 - 1995]Diplom-Studium und Wissenschaftlicher Mitarbeiter in der Hoch Energie Physik,
Dortmund
[1986 - 1991] Liscens-es-science in Physik und Chemie von der
Universität Abdelmalek Essadi, Tetouan (Marrokko) [Link]

Ausgewählte Publikationen (Medizin/Bioinformatik/Biostatistik)

[1] Pejchinovski, M., Siwy, J., Metzger, J., Dakna, M., Mischak, H., Klein, J., Jankowski, V., Bae, K. T., Chapman, A. B., and Kistler, A. D. (2017). Urine peptidome analysis predicts risk of end-stage renal disease and reveals proteolytic pathways involved in autosomal dominant polycystic kidney disease progression. Nephrol. Dial. Transplant., 32(3):487--497.

[2] Carrick, E., Vanmassenhove, J., Glorieux, G., Metzger, J., Dakna, M., Pejchinovski, M., Jankowski, V., Mansoorian, B., Husi, H., Mullen, W., Mischak, H., Vanholder, R., and Van Biesen, W. (2016). Development of a MALDI MS-based platform for early detection of acute kidney injury. Proteomics Clin Appl, 10(7):732--742.

[3] Schonemeier, B., Metzger, J., Klein, J., Husi, H., Bremer, B., Armbrecht, N., Dakna, M., Schanstra, J. P., Rosendahl, J., Wiegand, J., Jager, M., Mullen, W., Breuil, B., Plentz, R. R., Lichtinghagen, R., Brand, K., Kuhnel, F., Mischak, H., Manns, M. P., and Lankisch, T. O. (2016). Urinary Peptide Analysis Differentiates Pancreatic Cancer From Chronic Pancreatitis. Pancreas, 45(7):1018--1026.

[4] Frantzi, M., van Kessel, K. E., Zwarthoff, E. C., Marquez, M., Rava, M., Malats, N., Merseburger, A. S., Katafigiotis, I., Stravodimos, K., Mullen, W., Zoidakis, J., Makridakis, M., Pejchinovski, M., Critselis, E., Lichtinghagen, R., Brand, K., Dakna, M., Roubelakis, M. G., Theodorescu, D., Vlahou, A., Mischak, H., and Anagnou, N. P. (2016). Development and Validation of Urine-based Peptide Biomarker Panels for Detecting Bladder Cancer in a Multi-center Study. Clin. Cancer Res., 22(16):4077--4086.

[5] Bhat, A., Dakna, M., and Mischak, H. (2015). Integrating proteomics profiling data sets: a network perspective. Methods Mol Biol, 1243:237--53.

[6] Gleiss, A., Dakna, M., Mischak, H., and Heinze, G. (2015). Two-group comparisons of zero-inflated intensity values: the choice of test statistic matters. Bioinformatics, 31(14):2310--7.

[7] Schanstra, J. P., Zurbig, P., Alkhalaf, A., Argiles, A., Bakker, S. J., Beige, J., Bilo, H. J., Chatzikyrkou, C., Dakna, M., Dawson, J., Delles, C., Haller, H., Haubitz, M., Husi, H., Jankowski, J., Jerums, G., Kleefstra, N., Kuznetsova, T., Maahs, D. M., Menne, J., Mullen, W., Ortiz, A., Persson, F., Rossing, P., Ruggenenti, P., Rychlik, I., Serra, A. L., Siwy, J., Snell-Bergeon, J., Spasovski, G., Staessen, J. A., Vlahou, A., Mischak, H., and Vanholder, R. (2015). Diagnosis and prediction of ckd progression by assessment of urinary peptides. J Am Soc Nephrol, 26(8):1999--2010.

[8] Nkuipou-Kenfack, E., Bhat, A., Klein, J., Jankowski, V., Mullen, W., Vlahou, A., Dakna, M., Koeck, T., Schanstra, J. P., Zurbig, P., Rudolph, K. L., Schumacher, B., Pich, A., and Mischak, H. (2015). Identification of ageing-associated naturally occurring peptides in human urine. Oncotarget, 6(33):34106--34117.

[9] Chinello, C., Cazzaniga, M., De Sio, G., Smith, A. J., Gianazza, E., Grasso, A., Rocco, F., Signorini, S., Grasso, M., Bosari, S., Zoppis, I., Dakna, M., van der Burgt, Y. E., Mauri, G., and Magni, F. (2014). Urinary signatures of renal cell carcinoma investigated by peptidomic approaches. PLoS One, 9(9):e106684.

[10] Frantzi, M., Metzger, J., Banks, R. E., Husi, H., Klein, J., Dakna, M., Mullen, W., Cartledge, J. J., Schanstra, J. P., Brand, K., Kuczyk, M. A., Mischak, H., Vlahou, A., Theodorescu, D., and Merseburger, A. S. (2014). Discovery and validation of urinary biomarkers for detection of renal cell carcinoma. J Proteomics, 98:44--58.

[11] Nkuipou-Kenfack, E., Duranton, F., Gayrard, N., Argiles, A., Lundin, U., Weinberger, K. M., Dakna, M., Delles, C., Mullen, W., Husi, H., Klein, J., Koeck, T., Zurbig, P., and Mischak, H. (2014). Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease. PLoS One, 9(5):e96955.

[12] Stalmach, A., Johnsson, H., McInnes, I. B., Husi, H., Klein, J., Dakna, M., Mullen, W., Mischak, H., and Porter, D. (2014). Identification of urinary peptide biomarkers associated with rheumatoid arthritis. PLoS One, 9(8):e104625.

[13] Argiles, A., Siwy, J., Duranton, F., Gayrard, N., Dakna, M., Lundin, U., Osaba, L., Delles, C., Mourad, G., Weinberger, K. M., and Mischak, H. (2013). Ckd273, a new proteomics classifier assessing ckd and its prognosis. PLoS One, 8(5):e62837.

[14] Klein, J., Lacroix, C., Caubet, C., Siwy, J., Zurbig, P., Dakna, M., Muller, F., Breuil, B., Stalmach, A., Mullen, W., Mischak, H., Bandin, F., Monsarrat, B., Bascands, J. L., Decramer, S., and Schanstra, J. P. (2013). Fetal urinary peptides to predict postnatal outcome of renal disease in fetuses with posterior urethral valves (puv). Sci Transl Med, 5(198):198ra106.

[15] Metzger, J., Negm, A. A., Plentz, R. R., Weismuller, T. J., Wedemeyer, J., Karlsen, T. H., Dakna, M., Mullen, W., Mischak, H., Manns, M. P., and Lankisch, T. O. (2013). Urine proteomic analysis differentiates cholangiocarcinoma from primary sclerosing cholangitis and other benign biliary disorders. Gut, 62(1):122--30.

[16] Molin, L., Seraglia, R., Lapolla, A., Ragazzi, E., Gonzalez, J., Vlahou, A., Schanstra, J. P., Albalat, A., Dakna, M., Siwy, J., Jankowski, J., Bitsika, V., Mischak, H., Zurbig, P., and Traldi, P. (2012). A comparison between maldi-ms and ce-ms data for biomarker assessment in chronic kidney diseases. J Proteomics, 75(18):5888--97.

[17] Dakna, M., Harris, K., Kalousis, A., Carpentier, S., Kolch, W., Schanstra, J. P., Haubitz, M., Vlahou, A., Mischak, H., and Girolami, M. (2010). Addressing the challenge of defining valid proteomic biomarkers and classifiers. BMC Bioinformatics, 11:594.

[18] Good, D. M., Zurbig, P., Argiles, A., Bauer, H. W., Behrens, G., Coon, J. J., Dakna, M., Decramer, S., Delles, C., Dominiczak, A. F., Ehrich, J. H., Eitner, F., Fliser, D., Frommberger, M., Ganser, A., Girolami, M. A., Golovko, I., Gwinner, W., Haubitz, M., Herget-Rosenthal, S., Jankowski, J., Jahn, H., Jerums, G., Julian, B. A., Kellmann, M., Kliem, V., Kolch, W., Krolewski, A. S., Luppi, M., Massy, Z., Melter, M., Neususs, C., Novak, J., Peter, K., Rossing, K., Rupprecht, H., Schanstra, J. P., Schiffer, E., Stolzenburg, J. U., Tarnow, L., Theodorescu, D., Thongboonkerd, V., Vanholder, R., Weissinger, E. M., Mischak, H., and Schmitt-Kopplin, P. (2010). Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Mol Cell Proteomics, 9(11):2424--37.

[19] Mischak, H., Allmaier, G., Apweiler, R., Attwood, T., Baumann, M., Benigni, A., Bennett, S. E., Bischoff, R., Bongcam-Rudloff, E., Capasso, G., Coon, J. J., D'Haese, P., Dominiczak, A. F., Dakna, M., Dihazi, H., Ehrich, J. H., Fernandez-Llama, P., Fliser, D., Frokiaer, J., Garin, J., Girolami, M., Hancock, W. S., Haubitz, M., Hochstrasser, D., Holman, R. R., Ioannidis, J. P., Jankowski, J., Julian, B. A., Klein, J. B., Kolch, W., Luider, T., Massy, Z., Mattes, W. B., Molina, F., Monsarrat, B., Novak, J., Peter, K., Rossing, P., Sanchez-Carbayo, M., Schanstra, J. P., Semmes, O. J., Spasovski, G., Theodorescu, D., Thongboonkerd, V., Vanholder, R., Veenstra, T. D., Weissinger, E., Yamamoto, T., and Vlahou, A. (2010). Recommendations for biomarker identification and qualification in clinical proteomics. Sci Transl Med, 2(46):46ps42.

[20] Dakna, M., He, Z., Yu, W. C., Mischak, H., and Kolch, W. (2009). Technical, bioinformatical and statistical aspects of liquid chromatography-mass spectrometry (lc-ms) and capillary electrophoresis-mass spectrometry (ce-ms) based clinical proteomics: a critical assessment. J Chromatogr B Analyt Technol Biomed Life Sci, 877(13):1250--8.

[21] Haubitz, M., Good, D. M., Woywodt, A., Haller, H., Rupprecht, H., Theodorescu, D., Dakna, M., Coon, J. J., and Mischak, H. (2009). Identification and validation of urinary biomarkers for differential diagnosis and evaluation of therapeutic intervention in anti-neutrophil cytoplasmic antibody-associated vasculitis. Mol Cell Proteomics, 8(10):2296--307.

[22] Kistler, A. D., Mischak, H., Poster, D., Dakna, M., Wuthrich, R. P., and Serra, A. L. (2009). Identification of a unique urinary biomarker profile in patients with autosomal dominant polycystic kidney disease. Kidney Int, 76(1):89--96.

[23] Zurbig, P., Decramer, S., Dakna, M., Jantos, J., Good, D. M., Coon, J. J., Bandin, F., Mischak, H., Bascands, J. L., and Schanstra, J. P. (2009). The human urinary proteome reveals high similarity between kidney aging and chronic kidney disease. Proteomics, 9(8):2108--17.

[24] Coon, J. J., Zurbig, P., Dakna, M., Dominiczak, A. F., Decramer, S., Fliser, D., Frommberger, M., Golovko, I., Good, D. M., Herget-Rosenthal, S., Jankowski, J., Julian, B. A., Kellmann, M., Kolch, W., Massy, Z., Novak, J., Rossing, K., Schanstra, J. P., Schiffer, E., Theodorescu, D., Vanholder, R., Weissinger, E. M., Mischak, H., and Schmitt-Kopplin, P. (2008). Ce-ms analysis of the human urinary proteome for biomarker discovery and disease diagnostics. Proteomics Clin Appl, 2(7-8):964.

[25] Rossing, K., Mischak, H., Dakna, M., Zurbig, P., Novak, J., Julian, B. A., Good, D. M., Coon, J. J., Tarnow, L., and Rossing, P. (2008). Urinary proteomics in diabetes and ckd. J Am Soc Nephrol, 19(7):1283--90.