Prof. Ingo Roeder, Ph.D.
© P.Benjamin/NCTDD
Chair for Medical Biometry and Statistics
NameMr Prof. Dr. rer. med. Ingo Röder
Institute Director
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Prof. Ingo Roeder is Head of the Institute for Medical Informatics and Biometry. He is a member of the Carl Gustav Carus Medical Faculty at the Technische Universität Dresden. In particular, he holds the Chair for Medical Statistics and Biometry. Since 2015 Prof. Roeder has been scientific head of the Core Unit for Data Management and Analytics (DMA) at the National Centre for Tumor Diseases (NCT) at the partner site Dresden. Between 2014 and 2018 he acted as CIO of the TU Dresden School of Medicine. Since 2018 he ihas been dean of studies at the Faculty of Medicine.
Prof. Roeder’s research focus covers the following areas:
Theoretical Biology/System medicine:
- Application of mathematical models in the context of treatment optimisation/model-based experimental/study design (e.g. regarding CML, AML, T-PLL)
- Dynamics of molecular regulation networks
- Theoretical concepts of stem cell organisation (theoretical setm cell biology)
- Clonal competition phenomena and stem cell/niche interactions
Biostatistics/Bioinformatics:
- Statistical modelling (e.g. mixed-effect models)
- Analysis of cellular genealogies
- Analysis of single cell tracking data
- Model-based trial design
- Integrative analysis of molecular data (e.g. NGS-based)
Medical Informatics:
- Data integration models
- „Big Data“ in oncology
- Integration of model predictions in processes of clinical decision-making
Publications
2019
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The prevalence of headache in German pupils of different ages and school types, 1 Jul 2019, In: Cephalalgia. 39, 8, p. 1030-1040, 11 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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To Cure or Not to Cure: Consequences of Immunological Interactions in CML Treatment, Jul 2019, In: Bulletin of mathematical biology. 81, 7, p. 2345-2395, 51 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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The prognostic potential of monitoring disease dynamics in NPM1-positive acute myeloid leukemia, 1 Jun 2019, In: Leukemia. 33, 6, p. 1531-1534, 4 p.Electronic (full-text) versionResearch output: Contribution to journal > Letter
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Automating pollen counting using deep learning, 2019, In: Allergo Journal. 28, p. 74-75, P 2.7Electronic (full-text) versionResearch output: Contribution to journal > Meeting abstract
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Statistical and mathematical modeling of spatiotemporal dynamics of stem cells, 2019, Methods in Molecular Biology: Stem Cell Mobilization. Vol. 2017. p. 219-243, 25 p.Research output: Contribution to book/conference proceedings/anthology/report > Chapter in book/Anthology/Report
2018
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Reduced tyrosine kinase inhibitor dose is predicted to be as effective as standard dose in chronic myeloid leukemia: a simulation study based on phase III trial data, Nov 2018, In: Haematologica. 103, 11, p. 1825-1834, 10 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Paracrine mechanisms in early differentiation of human pluripotent stem cells: Insights from a mathematical model, Oct 2018, In: Stem cell research. 32, p. 1-7, 7 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Quantitative prediction of long-term molecular response in TKI-treated CML - Lessons from an imatinib versus dasatinib comparison, 17 Aug 2018, In: Scientific reports. 8, 1, 12330Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Metabolism is the tie: The Bertalanffy-type cancer growth model as common denominator of various modelling approaches, May 2018, In: BioSystems. 167, p. 1-23, 23 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Whither systems medicine?, 2 Mar 2018, In: Experimental and Molecular Medicine. 50, 3, e453Electronic (full-text) versionResearch output: Contribution to journal > Review article
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