SEEK ID: https://seek.lisym.org/people/146
Location:
Germany
ORCID: Not specified
Joined: 1st Apr 2020
Expertise: Not specified
Tools: Not specified
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- Programmes (1)
- Projects (3)
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LiSyM-Krebs ist ein nationales Forschungsnetz zur Früherkennung und Prävention von Leberkrebs, das unter Verwendung des systemmedizinischen Forschungsansatzes die komplexen, dynamischen Prozesse der Krankheitsprogression analysiert, um ausgehend von den Erkenntnissen aus dem Forschungsnetz LiSyM die Entstehung von Leberkrebs besser zu verstehen, vorherzusagen und im besten Fall sogar zu verhindern. LiSyM-Krebs setzt die erfolgreichen Forschungsaktivitäten der BMBF-Vorgängerprogramme ...
Projects: LiSyM-Krebs Partnering, Forschungsnetzwerk LiSyM-Krebs, SMART-NAFLD, DEEP-HCC network, C-TIP-HCC network
Web page: https://www.lisym-cancer.org
DEEP-HCC - Detailed Analysis of the Spatial Organization of the Development of Hepatocellular Carcinoma
Programme: LiSyM-Krebs - Systemmedizinisches Forschungsnetz zur Früherkennung und Prävention von Leberkrebs
Public web page: Not specified
Organisms: Homo sapiens, Mus musculus
This generic project is intended to be a forum for all LiSyM partner and external stakeholders interested in participating in the BMBF initiative LiSyM-Krebs.
Programme: LiSyM-Krebs - Systemmedizinisches Forschungsnetz zur Früherkennung und Prävention von Leberkrebs
Public web page: https://www.ptj.de/projektfoerderung/gesundheitsforschung/lisym-krebs
Organisms: Not specified
SMART-NAFLD : A Systems Medicine Approach to Early Detection and Prevention of Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease
The massive increase in obesity is leading to an alarming rise in non-alcoholic liver disease (NAFLD). This development will lead to a dramatic increase in liver diseases such as hepatocellular carcinoma (HCC). A particular challenge is that NAFLD-associated HCCs, for reasons still unknown, not only occur in association with advanced liver fibrosis/cirrhosis, ...
Programme: LiSyM-Krebs - Systemmedizinisches Forschungsnetz zur Früherkennung und Prävention von Leberkrebs
Public web page: Not specified
Organisms: Mus musculus, Homo sapiens
To investigate the underlying molecular principles of metabolic and morphogenic zonation of the human liver lobule, we generated an integrated epigenetic map across three zones (pericentral, intermediate and periportal) by methylation and transcriptomic analysis of hepatocytes captured by laser micro-dissection. We observe a deep link between epigenetic zonation of human liver and a zonated expression of metabolic and morphogenic pathways: Key transcriptionally zonated enzymes in xenobiotic and ...
Submitter: Mario Brosch
Studies: Integrated epigenetic map across three hepatic zones (pericentral, inte...
Assays: DNA-methylation at binding sites of uniformly expressed transcription fa..., DNA-methylation at binding sites of uniformly expressed transcription fa..., DNA-methylation at binding sites of uniformly expressed transcription fa..., Transcriptomic analysis of hepatocytes ( hepatic zone: intermediate (IZ), Transcriptomic analysis of hepatocytes ( hepatic zone: periportal (PP), Transcriptomic analysis of hepatocytes ; hepatic zone: pericentral (CV)
Snapshots: No snapshots
ODE model describes dynamics of IFNalpha-induced signaling in Huh7.5 cells for a time scale up to 32 hours after stimulation with IFNalpha. The model consists of an IFN receptor model, formation/degradation and cytoplasmic/nuclear shuttling of STAT1-homodimers, STAT1-STAT2-heterodimers and STAT1-STAT2-IRF9 (ISGF3) complexes. On top, formation of feedback proteins STAT1, STAT2, IRF9, USP18, SOCS1, SOCS3 and IRF2 and corresponding influences on IFNalpha signaling dynamics was incorporated. The model ...
Creators: Jens Timmer, Ursula Klingmüller, Daniel Seehofer, Marcus Rosenblatt, Krishna Kumar Tiwari, Frédérique Kok
Submitter: Olga Krebs
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
Organism: Not specified
Investigations: 1 hidden item
Studies: 1 hidden item
Assays: 1 hidden item
Abstract (Expand)
Authors: L. Seidemann, S. Prinz, J. C. Scherbel, C. Gotz, D. Seehofer, G. Damm
Date Published: 20th Jan 2023
Publication Type: Journal
PubMed ID: 36660192
Citation: EXCLI J. 2023 Jan 4;22:12-34. doi: 10.17179/excli2022-5459. eCollection 2023.
Abstract (Expand)
Authors: Paula Heinke, Fabian Rost, Julian Rode, Palina Trus, Irina Simonova, Enikő Lázár, Joshua Feddema, Thilo Welsch, Kanar Alkass, Mehran Salehpour, Andrea Zimmermann, Daniel Seehofer, Göran Possnert, Georg Damm, Henrik Druid, Lutz Brusch, Olaf Bergmann
Date Published: 1st Jun 2022
Publication Type: Journal
DOI: 10.1016/j.cels.2022.05.001
Citation: Cell Systems 13(6):499-507.e12
Abstract (Expand)
Authors: Andrea Zimmermann, René Hänsel, Kilian Gemünden, Victoria Kegel-Hübner, Jonas Babel, Hendrik Bläker, Madlen Matz-Soja, Daniel Seehofer, Georg Damm
Date Published: 1st Apr 2021
Publication Type: Journal
DOI: 10.3390/biomedicines9040406
Citation: Biomedicines 9(4):406
Abstract (Expand)
Authors: F. Kok, M. Rosenblatt, M. Teusel, T. Nizharadze, V. Goncalves Magalhaes, C. Dachert, T. Maiwald, A. Vlasov, M. Wasch, S. Tyufekchieva, K. Hoffmann, G. Damm, D. Seehofer, T. Boettler, M. Binder, J. Timmer, M. Schilling, U. Klingmuller
Date Published: 23rd Jul 2020
Publication Type: Journal
PubMed ID: 32696599
Citation: Mol Syst Biol. 2020 Jul;16(7):e8955. doi: 10.15252/msb.20198955.
Abstract (Expand)
Authors: Erik Kolbe, Susanne Aleithe, Christiane Rennert, Luise Spormann, Fritzi Ott, David Meierhofer, Robert Gajowski, Claus Stöpel, Stefan Hoehme, Michael Kücken, Lutz Brusch, Michael Seifert, Witigo von Schoenfels, Clemens Schafmayer, Mario Brosch, Ute Hofmann, Georg Damm, Daniel Seehofer, Jochen Hampe, Rolf Gebhardt, Madlen Matz-Soja
Date Published: 1st Dec 2019
Publication Type: Not specified
DOI: 10.1016/j.celrep.2019.11.104
Citation: Cell Reports 29(13) : 4553