Seifert Lab: Medical Bioinformatics
The fast progress in the development of experimental technologies enables to measure molecular data of complex diseases with unprecedented detail. The analysis of such heterogeneous data sets requires specific bioinformatic tools to disentangle the complex interplay of different regulatory layers associated with disease-causing processes.
The focus of the research group Medical Bioinformatics is on the analysis of molecular high-throughput data for specific research questions connected to human diseases and on the development of corresponding innovative bioinformatic approaches and methods for the integrative analysis of the different molecular layers of such data sets. The research group can also offer support for data analyses based on bioinformatic consulting and extended service projects.
Research and service focus
- Analysis of molecular high-throughput data (e.g. transcriptome, epigenome, genome, proteome, metabolome) measured by bulk sequencing, single-cell sequencing, microarrays or other technologies
- Development of network-based methods and probabilistic models for the integrative analysis of heterogeneous molecular high-throughput data
- Identification and characterization of molecular alterations and their associations with subgroups and clinical data
- Application of existing and newly developed data analysis strategies for computational cancer research (e.g. melanoma, astrocytoma, oligodendroglioma, leukemia, head and neck cancer, ovarian cancer)
Selected Projects
- Junior Associations MelBrainSys — Model-based prediction and experimental validation of novel therapeutic interventions for melanoma brain metastases (BMBF)
- Reconstruction of the evolutionary development of ovarian cancer
- Identification of novel cancer candidate genes for oligodendrogliomas
- Comparative preclinical drug response analysis of T-cell prolymphocytic leukemia
- Identification and characterization of gene expression differences between melanoma metastases in different organs
- Determination of molecular signatures associated with survival of acute myeloid leukemia
- Single-cell based transcriptome comparisons of brain and non-brain metastases of melanomas
Group leader
© Michael Seifert
Group leader
NameMr PD Dr. rer. nat. habil. Michael Seifert
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Members of the research group
© Luca Penso Dolfin
Research fellow
NameMr Dr. Luca Penso Dolfin
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Students (MD/ Ph.D. students, student assistants)
© Natalie Labitzke
MD student
NameMs Natalie Labitzke
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© Niclas Lange
MD student
NameMr Niclas Lange
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© Inja Lenhardt
MD student
NameMs J. M. Inja Lenhardt
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© Xuliang Xu
research assistant
NameMr Xuliang Xu B.Sc.
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Former staff members
© Felix Broghammer
Research fellow (external: OncoRay)
NameMr Felix Broghammer M.Sc.
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© Felicitas-Berenike Broll
MD student
NameMs Felicitas-Berenike Broll
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© Julia Figueroa Martinez
Master student
NameMs Julia Figueroa Martinez
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MD student
NameMr Josef Gladitz
Else-Kröner-Stiftung
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© Konrad Gruetzmann
Research fellow
NameMr Dr. rer. nat. Konrad Grützmann
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© Cosima Hufnagel
MD student
NameMs Cosima Hufnagel
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© Theresa Kraft
Research fellow
NameMs Theresa Kraft M.Sc.
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© Chris Lauber
Research fellow
NameMr Dr. Chris Lauber
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student assistant
NameMs Olena Maiakovska B.Sc.
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student assistant
NameMr Assad Majid B.Sc.
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Research fellow
NameMr Dr. rer. nat. Nathan Mikhaylenko
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Ph.D. student
NameMr Adrian Ortiz Cervantes M.Sc.
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© Pirasteh Pahlavan
Research fellow (external: NCT)
NameMs Dr. rer. nat. Pirasteh Pahlavan
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© Michael Rank
Research fellow
NameMr Michael Rank M.Sc.
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© Lisa Schöne
Research fellow (external: NCT)
NameMs Lisa Schöne M.Sc.
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© Annemarie Schwarz
MD student
NameMs Annemarie Schwarz
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MD student
NameMs Lisa Sturm
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© Marc-Christoph Wagner
Research fellow
NameMr Marc-Christoph Wagner M.Sc.
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Publications of the lab
2024
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Personalized identification and characterization of genome-wide gene expression differences between patient-matched intracranial and extracranial melanoma metastasis pairs, 24 Apr 2024, In: Acta neuropathologica communications. 12, 1, p. 67, 67Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Resistance of HNSCC cell models to pan-FGFR inhibition depends on the EMT phenotype associating with clinical outcome, 21 Feb 2024, In: Molecular cancer. 23(2024), 1, 25 p., 39Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups, 17 Feb 2024, In: Computational and Structural Biotechnology Journal. 23 (2024), p. 1036-1050, 15 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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β1 integrin mediates unresponsiveness to PI3Kα inhibition for radiochemosensitization of 3D HNSCC models, Feb 2024, In: Biomedicine & pharmacotherapy. 171 (2024), 13 p., 116217Electronic (full-text) versionResearch output: Contribution to journal > Research article
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The dopamine receptor D1 inhibitor, SKF83566, suppresses GBM stemness and invasion through the DRD1-c-Myc-UHRF1 interactions, 22 Jan 2024, In: Journal of Experimental and Clinical Cancer Research. 43(2024), 1, 17 p., 25Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Comparative analysis of neurofilaments and biomarkers of muscular damage in amyotrophic lateral sclerosis, 2024, In: Brain Communications. 6, 5, fcae288Electronic (full-text) versionResearch output: Contribution to journal > Research article
2023
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Screen time and sleep among medical students in Germany, 19 Sep 2023, In: Scientific reports. 13, 1, 15462Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification, 2 Aug 2023, In: Nature communications. 14, 1, 4632Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Identification of Epigenetically Regulated Genes Distinguishing Intracranial from Extracranial Melanoma Metastases, Jul 2023, In: Journal of Investigative Dermatology. 143, 7, p. 1233-1245.e17, 30 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
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Plasma extracellular vesicle messenger RNA profiling identifies prognostic EV signature for non-invasive risk stratification for survival prediction of patients with pancreatic ductal adenocarcinoma, 3 Feb 2023, In: Journal of hematology & oncology. 16 (2023), 1, 19 p., 7Electronic (full-text) versionResearch output: Contribution to journal > Research article
This information is provided by the FIS.