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Medical Informatics and Biometry

The Institute for Medical Informatics and Biometry (IMB) is a cross-disciplinary institute with diverse research activities at the intersection of medicine, biology, mathematics, statistics, and bioinformatics. Using theoretical methods and computer-assisted approaches the IMB pursues and supports the planning, implementation, analysis, and interpretation of basic and clinical research projects at the Faculty of Medicine and other institutions of the TU Dresden.

Research areas (Selection):

  • Systems biology, systems medicine and mathematical modelling: This research focus deals with the development and the application of mathematical models in different areas of the life sciences. Beside basic research questions in biology (e.g. self-renewal and differentiation control of stem cells, stem cell – niche interactions or cell migration), we also address topics with an explicit clinical relation (e.g. disease and treatment models of different leukemia types and other malignancies). It is our objective to understand and predict the mechanisms that underlie dynamic physiological and pathophysiological processes by the application of analytic approaches and by computer simulation.
     
  • Medical Biometry and Bioinformatics: In this area we focus on the development and application of innovative data analysis methods, including the fields of experimental and clinical trial design. Beside methods from “classical” biometry / statistics, we are also working on bioinformatics methods including techniques for the integrative analysis of molecular high-throughput data and for the analysis of imaging data.
     
  • Medical Informatics: Modern diagnostic procedures and/or measurement techniques provide ever-increasing amounts of data (e.g. individual genomic profiles, multi-modal image data, etc.). We are specifically concerned with the development and implementation of integrated data storage and analysis methods, which allow to extract quantitative information out of clinical trials, to analyse them, and to use the generated knowledge directly for the design of new clinical trials.
Roeder 1

Fig 1: Concept (left) and simulation results (right) of a systems medical approach for tyrosine kinase inhibitor (TKI)-treated chronic myeloid leukaemia (CML). Based on clinical data (ie., polymerase chain reaction (PCR) measurements of the tumor load), a mechanistic mathematical model is used to estimate and predict the disease kinetics in individual patients. The simulation results (right) shown, how different assumptions on the immune response affects the relapse risk for individual patients after stopping the TKI treatment. @ IMB, Faculty of Medicine, TU Dresden

Roeder 2

Fig 2. Systems biological applications use mathematical models and computational methods, such as computer simulations to quantitatively describe and predict biological processes. The graphic shows the model structure (left) and simulation results (right) of the effect of transcription factor regulation on the differentiation mouse embryonic stem (ES) cells. (cf. Herberg et al. JRSoc Interface. 2016; Herberg & Roeder, Development, 2015) @ IMB, Faculty of Medicine, TU Dresden

You can find a complete publication list at www.tu-dresden.de/med/mf/imb.

2020

Bondarieva A, Raveendran K, Telychko V, Rao HBDP, Ravindranathan R, Zorzompokou C, Finsterbusch F, Dereli I, Papanikos F, Tränkner D, Schleiffer A, Fei JF, Klimova A, Ito M, Kulkarni DS, Roeder I, Hunter N, Tóth A. Proline-rich protein PRR19 functions with cyclin-like CNTD1 to promote meiotic crossing over in mouse. Nature communications 11 (2020) 3101, DOI Link

Erdmann K, Salomo K, Klimova A, Heberling U, Lohse-Fischer A, Fuehrer R, Thomas C, Roeder I, Froehner M, Wirth MP, Fuessel S. Urinary MicroRNAs as Potential Markers for Non-Invasive Diagnosis of Bladder Cancer. International journal of molecular sciences 21 (2020), DOI Link

Gottschalk A, Glauche I, Cicconi S, Clark RE, Roeder I. Molecular monitoring during dose reduction predicts recurrence after TKI cessation in CML. Blood 135 (2020) 766-769, DOI Link

Hähnel T, Baldow C, Guilhot J, Guilhot F, Saussele S, Mustjoki S, Jilg S, Jost PJ, Dulucq S, Mahon FX, Roeder I, Fassoni AC, Glauche I. Model-based inference and classification of immunological control mechanisms from TKI cessation and dose reduction in CML patients. Cancer research 80 (2020) 2394-2406, DOI Link

Hattab G, Ahlfeld T, Klimova A, Koepp A, Schuerer M, Speidel S. Uniaxial compression testing and Cauchy stress modeling to design anatomical silicone replicas. Scientific reports 10 (2020) 11849, DOI Link

Hoffmann K, Cazemier K, Baldow C, Schuster S, Kheifetz Y, Schirm S, Horn M, Ernst T, Volgmann C, Thiede C, Hochhaus A, Bornhäuser M, Suttorp M, Scholz M, Glauche I, Loeffler M, Roeder I. Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology. BMC medical informatics and decision making 20 (2020) 28, DOI Link

Hoffmann H, Thiede C, Glauche I, Bornhaeuser M, Roeder I. Differential response to cytotoxic therapy explains treatment dynamics of acute myeloid leukaemia patients: insights from a mathematical modelling approach. Journal of the Royal Society, Interface 17 (2020) 20200091, DOI Link

Kloenne M, Niehaus S, Lampe L, Merola A, Reinelt J, Roeder I, Scherf N. Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes. Scientific reports 10 (2020) 10712, DOI Link

Lauber C, Correia N, Trumpp A, Rieger MA, Dolnik A, Bullinger L, Roeder I, Seifert M. Survival differences and associated molecular signatures of DNMT3A-mutant acute myeloid leukemia patients. Scientific reports 10 (2020) 12761, DOI Link

Machova Polakova K, Zizkova H, Zuna J, Motlova E, Hovorkova L, Gottschalk A, Glauche I, Koblihova J, Pecherkova P, Klamova H, Stastna Markova M, Srbova D, Benesova A, Polivkova V, Jurcek T, Zackova D, Mayer J, Ernst T, Mahon FX, Saussele S, Roeder I, Cross NCP, Hochhaus A. Analysis of chronic myeloid leukaemia during deep molecular response by genomic PCR: a traffic light stratification model with impact on treatment-free remission. Leukemia 34 (2020) 2113-2124, DOI Link

Roeder I, Glauche I. Overlooking the obvious? On the potential of treatment alterations to predict patient-specific therapy response. Experimental hematology (2020), DOI Link

2019

de Back W, Zerjatke T, Roeder I. Statistical and Mathematical Modeling of Spatiotemporal Dynamics of Stem Cells. Methods in Molecular Biology 2017 (2019) 219-243, DOI Link

Fassoni AC, Roeder I, Glauche I. To Cure or Not to Cure: Consequences of Immunological Interactions in CML Treatment. Bulletin of Mathematical Biology (2019) 1-51, DOI Link

Hoffmann H, Thiede C, Glauche I, Kramer M, Röllig C, Ehninger G, Bornhäuser M, Roeder I. The prognostic potential of monitoring disease dynamics in NPM1-positive acute myeloid leukemia. Leukemia 33 (2019) 1531-1534, DOI Link

Nieswald V, Richter M, Berner R, von der Hagen M, Klimova A, Roeder I, Koch T, Sabatowski R, Gossrau G. The prevalence of headache in German pupils of different ages and school types. Cephalalgia 39 (2019) , DOI Link

Romero Starke K, Seidler A, Hegewald J, Klimova A, Palmer K. Retirement and decline in episodic memory: analysis from a prospective study of adults in England. International Journal of Epidemiology 48 (2019) 1925-1936, DOI Link

Seidlitz T, Chen YT, Uhlemann H, Schölch S, Kochall S, Merker SR, Klimova A, Henning A, Schweitzer C, Pape K, Baretton GB, Welsch T, Aust DE, Weitz J, Koo BK, Stange DE. Mouse Models of Human Gastric Cancer Subtypes With Stomach-Specific CreERT2-Mediated Pathway Alterations. Gastroenterology 157 (2019) 1599-1614.e2, DOI Link

Zakrzewski F, de Back W, Weigert M, Wenke T, Zeugner S, Mantey R, Sperling C, Friedrich K, Roeder I, Aust D, Baretton G, Hönscheid P
Automated detection of the HER2 gene amplification status in Fluorescence in situ hybridization images for the diagnostics of cancer tissues. Scientific Reports 9 (2019), DOI Link

Fassoni AC, Baldow C, Roeder I, Glauche I. Reduced tyrosine kinase inhibitor dose is predicted to be as effective as standard dose in chronic myeloid leukemia: A simulation study based on phase 3 trial data. Haematologica 103 (2018) 1825-1834, DOI Link

2018

Fassoni AC, Baldow C, Roeder I, Glauche I. Reduced tyrosine kinase inhibitor dose is predicted to be as effective as standard dose in chronic myeloid leukemia: A simulation study based on phase 3 trial data. Haematologica 103 (2018) 1825-1834, DOI Link

Glauche I, Kuhn M, Baldow C, Schulze P, Rothe T, Liebscher H, Roy A, Wang X, Roeder I. Quantitative prediction of long-term molecular response in TKI-treated CML - Lessons from an imatinib versus dasatinib comparison.
Scientific Reports 8 (2018) 12330, DOI Link

2017

Baldow C, Salentin S, Schroeder M, Roeder I, Glauche I. MAGPIE: Simplifying access and execution of computational models in the life sciences.
PLOS Computational Biology 13 (2017) 1-11, DOI Link

Proschmann R, Baldow C, Rothe T, Suttorp M, Thiede C, Tauer JT, Müller MC, Hochhaus A, Roeder I, Glauche I. Response dynamics of pediatric patients with chronic myeloid leukemia on imatinib therapy. Haematologica 102 (2017) e39-e42, DOI Link