Prof. Dr. Michael Altenbuchinger

Telephone: 0551/39-14919

E-Mail: michael.altenbuchinger@bioinf.med.uni-goettingen.de

Location: Goldschmidtstr. 1, 2. OG, Room: 2.116

Orcid: https://orcid.org/0000-0003-1102-6532

Curriculum Vitae

Research Experience

06/2021 – Now  W2 professor (tenure track), University Medical Center Goettingen, Institute of Medical Bioinformatics, Göttingen, Germany

02/2020 – 05/2021 Junior Research Group Leader

02/2019 – 01/2020 Postdoctoral Fellow (with Prof. J. Quackenbush), Harvard T.H. Chan School of Public Health, Department of Biostatistics, Boston, MA, USA

10/2014 – 01/2019  Postdoctoral Fellow (with Prof. R. Spang), University of Regensburg, Statistical Bioinformatics, Regensburg, Germany

04/2014 – 08/2014  Postdoctoral Fellow (with Prof. W. Weise), Technical University of Munich, Munich, Germany

02/2010 – 01/2014 Doctoral researcher (with W. Weise), Technical University of Munich, Munich, Germany

Education

02/2010 – 01/2014  Dr. rer. nat. (Physics), Thesis: Chiral Dynamics of Heavy­Light Mesons, Adviser: Prof. Wolfram Weise,Technical University of Munich, Munich, Germany

10/2004 – 11/2009  Dipl. Phys. (Univ.), Technical University of Munich, Munich, Germany

10/2003 – 07/2004 Vordiplom (FH) (Engineering Physics), Munich University of Applied Sciences, Munich, Germany

Grants

started in 05/2020 Project title: ”Digital Tissue Deconvolution ­ Aus Einzelzelldaten lernen”, DFG Sachmittelbeihilfe

started in 05/2020 Project title: ”CKDNapp: A toolbox for monitoring and tailoring treatment of chronic kidney disease patients ­ a personalized systems medicine approach”, Subproject ”Algorithms for the clinical decision support software CKDNapp” in the Junior consortium ”CKDNapp”, BMBF Juniorverbünde in der Systemmedizin

Awards

Best poster award, FOR 2127: Selection and adaptation during metastatic cancer progression, Regensburg, 2016

Publications

Original papers

R. D. Jachimowicz, W. Klapper, G. Glehr, H. Müller, H. Haverkamp, C. Thorns, ... & M. Altenbuchinger:
A. Rosenwald∗ . Gene expression­based outcome prediction in advanced stage classical Hodgkin lymphoma treated with BEACOPP.
Leukemia, 1­5, 2021.

W. X. Schulze, M. Altenbuchinger, M. He, M. Kränzlein & C. Zörb:
Proteome profiling of repeated drought stress reveals genotype­specific responses and memory effects in maize.
Plant Physiology and Biochemistry, 159, 67­79. 2021.

C. Nordmo, G. Glehr, M. Altenbuchinger, R. Spang, M. Ziepert, H. Horn, ... & H. Rauert­Wunderlich:
Identification of a miRNA based model to detect prognostic subgroups in patients with aggressive B­cell lymphoma.
Leukemia & Lymphoma, 1­15, 2020.

J. Reinders, M. Altenbuchinger, K. Limm, P. Schwarzfischer, T. Scheidt, ... & P. J. Oefner:
Platform independent protein­based cell­of­origin subtyping of diffuse large B­cell lymphoma in formalin­fixed paraffin­embedded tissue.
Scientific Reports, 10(1), 1­11, 2020.

M. Schön, J. Simeth, P. Heinrich, F. Görtler, S. Solbrig, T. Wettig, P. J. Oefner, M. Altenbuchinger, R. Spang: 
DTD: An R Package for Digital Tissue Deconvolution.
Journal of Computational Biology, 27(3), 1­4, 2020.

F. Görtler, M. Schön, J. Simeth, S. Solbrig, T. Wettig, P. J. Oefner, R. Spang, M. Altenbuchinger:
Loss­Function Learning for Digital Tissue Deconvolution.
Journal of Computational Biology, 27(3), 1­14, 2020.

M. Altenbuchinger† , H. U. Zacharias† , S. Solbrig, A. Schäfer, M. Büyüközkan, U. Schultheiß, F. Kotsis, A. Köttgen, R. Spang, P. J. Oefner, J. Krumsiek, W. Gronwald:
A multi­source data integration approach reveals novel associations between metabolites and renal outcomes in the German chronic Kidney Disease study.
Scientific Reports, 9, 13954, 2019.

A. Staiger† , M. Altenbuchinger† , M. Ziepert† , C. Kohler, H. Horn, M. Huttner, K. Huettl, G. Glehr, W. Klapper, J. Richter, M. Szczepanowski, H. Stein, A. Feller, P. Möller, M.L. Hansmann, V. Pöschel, G. Held, M. Loeffler, L. Trümper, T. Pukrop, A. Rosenwald, G. Ott, and R. Spang: 
A Novel Lymphoma­Associated Macrophage Interaction Signature (LAMIS) Provides Robust Risk Prognostication in Diffuse Large B­ Cell Lymphoma Clinical Trial Cohorts of the DSHNHL.
Leukemia, 1­10, 2019.

M. Wagner, R. Hänsel, S. Reinke, J. Richter, M. Altenbuchinger, U. Braumann, R. Spang, Markus Löffler, and W. Klapper: 
Automated macrophage counting in DLBCL tissue samples: a rof filter based approach.
MC: Biol Proced Online, 21(1), 13, 2019.

H. U. Zacharias, M. Altenbuchinger, U. T. Schultheiss, C. Samol, F. Kotsis, I. Poguntke, P. Sekula, J. Krumsiek, A. Köttgen, R. Spang, P. J. Oefner, W. Gronwald.
A novel metabolic signature to predict the requirement of dialysis or renal transplantation in patients with chronic kidney disease.
Journal of Proteome Research, 2019, DOI: 10.1021/acs.jproteome.8b00983.

F. Görtler, S. Solbrig, T. Wettig, P. J. Oefner, R. Spang, and M. Altenbuchinger:
Loss­function learning for digital tissue deconvolution.
In Proc. RECOMB 2018, 75­89, doi.org/10.1007/ 978­3­319­89929­9_5, 2018. (Acceptance rate: 20%)

S. Reinke, J. Richter, F. Fend, A. Feller, M. Hansmann, K. Hüttl, I. Oschlies, G. Ott, P. Möller, A, Rosenwald, H. Stein, M. Altenbuchinger, R. Spang, W. Klapper:
Round­robin test for the cell­of­origin classification of diffuse large B­cell lymphoma ­ a feasibility study using full slide staining.
Virchows Archiv, 1­9, 2018.

M. Altenbuchinger, P. Schwarzfischer, T. Rehberg, J. Reinders, C. W. Kohler, W. Gronwald, J. Richter, M. Szczepanowski, N. Masqué­Soler, W. Klapper, P. J. Oefner, and R. Spang:
Molecular signatures that can be transferred across different omics platforms.
Bioinformatics (Special issue: ISMB 2017 proceedings), 33(14): i333 – i340, 2017. (Acceptance rate: 16%)

L. Cascione, A. Rinaldi, A. Chiappella, I. Kwee, G. Ciccone, M. Altenbuchinger, C. W. Kohler, U. Vitolo, G. Inghirami, and F. Bertoni:
Diffuse large B cell lymphoma cell of origin by digital expression profiling in the REAL07 Phase 1­2 study.
British Journal of Haematology, doi: 10.1111/bjh.14817, 2017.

H. U. Zacharias, T. Rehberg, S. Mehrl, D. Richtmann, T. Wettig, P. J. Oefner, R. Spang, W. Gronwald, and M. Altenbuchinger :
Scale­invariant biomarker discovery in urine and plasma metabolite fingerprints.
J Proteome Res., doi: 10.1021/acs.jproteome.7b00325., 2017.

M. Szczepanowski, J. Lange, C. W. Kohler, N. Masqué­Soler, M. Zimmermann, S. M. Aukema, M. Altenbuchinger, T. Rehberg, F. Mahn, R. Siebert, R. Spang, B. Burkhardt, and W. Klapper.
Cell­of­origin classification by gene expression and MYC­rearrangements in diffuse large B­cell lymphoma of children and adolescents.
British Journal of Haematology, doi: 10.1111/bjh.14812, 2017.

M. Altenbuchinger† , T. Rehberg† , H. U. Zacharias, F. Stämmler, K. Dettmer, D. Weber, A. Hiergeist, A. Gessner, E. Holler, P. J. Oefner, and R. Spang.
Reference point insensitive molecular data analysis.
Bioinformatics, 33(2):219­226, 2017.

M. Altenbuchinger and L. S. Geng:
Off­shell effects on the interaction of Nambu­Goldstone bosons and D mesons.
Phys. Rev., D89(5):054008, 2014.

M. Altenbuchinger, L. S. Geng, and W. Weise:
Scattering lengths of Nambu­ Goldstone bosons off D mesons and dynamically generated heavy­light mesons.
Phys. Rev., D89(1):014026, 2014.

M. Altenbuchinger, L. S. Geng, and W. Weise: 
SU(3) breaking corrections to the D, D, B, and B decay constants.
Phys. Lett., B713:453­456, 2012.

M. Altenbuchinger, Ph. Hägler, W. Weise, and E. M. Henley.:
Spin structure of the nucleon: QCD evolution, lattice results and models.
Eur. Phys. J., A47:140, 2011.

L. S. Geng, M. Altenbuchinger, and W. Weise:
Light quark mass dependence of the D and Ds decay constants.
Phys. Lett., B696:390­395, 2011.

Reviews

M. Altenbuchinger, A. Weihs, J. Quackenbush, H. J. Grabe, H. U. Zacharias:
Gaussian and Mixed Graphical Models as (multi­)omics data analysis tools.
BBA ­ Gene Regulatory Mechanisms 1863, 194418, 2020.

H. U. Zacharias, M. Altenbuchinger, and W. Gronwald. Statistical Analysis of NMR Metabolic Fingerprints:
Established Methods and Recent Advances.
Metabolites, www.mdpi.com 2218­1989/8/3/47/pdf, 2018.

Other publications

A. M. Staiger, M. Altenbuchinger , M. Ziepert , et al.:
A New Stromal Signature Applicable to Formalin­Fixed Paraffin­Embedded Tissues Identifies Patients at Risk in Prospective Clinical Trials of the German High­Grade Non­Hodgkin Lymphoma Study Group.
Blood, 132 (Suppl 1) 343; DOI: 10.1182/blood­2018­99­112450

H. Cho, B. Berger, J. Peng, C. Galitzine, O. Vitek, P. M. Jean, B. Ileana, M. Cristea, F. Görtler, S. Solbrig, T. Wettig, P. J.Oefner, R. Spang, M. Altenbuchinger, R. Sarto, and others:
Principles of Systems Biology, No. 31. Cell Systems, 7(2), 133­135, 2018.

Professional Affiliations & Activities

09/2018 – Present  GMDS / IBS­DR working group ”Statistical Methods in Bioinformatics”, Leader of the working group

Workshop Organization

03/2019  ”Workshop on Computational Models in Biology and Medicine 2019” (BRICS, Braunschweig)

02/2020  ”Workshop on Computational Models in Biology and Medicine 2020” (University of Bonn, Bonn)

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