SEEK ID: https://seek.lisym.org/people/118
Location: Germany
ORCID: https://orcid.org/0000-0003-4517-1383
Joined: 18th Dec 2018
Expertise: Not specified
Tools: Not specified
Related items
- Programmes (2)
- Projects (7)
- Institutions (1)
- Investigations (1+2)
- Studies (1)
- Assays (0+2)
- Models (3+1)
- Publications (14)
- Presentations (1+12)
- Documents (0+2)
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
Liver Systems Medicine : striving to develop non-invasive methods for diagnosing and treating NAFLD by combining mathematical modeling and biological research. LiSyM, is a multidisciplinary research network, in which molecular and cell biologists, clinical researchers, pharmacologists and experts in mathematical modeling examine the liver in its entirety. LiSyM research focuses on the metabolic liver disease non-alcoholic fatty liver disease (NAFLD), which includes non-alcoholic steatohepatitis ...
Projects: LiSyM Core Infrastructure and Management (LiSyM-PD), LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI), LiSyM Pillar II: Chronic Liver Disease Progression (LiSyM-DP), LiSyM Pillar III: Regeneration and Repair in Acute-on-Chronic Liver Failure (LiSyM-ACLF), LiSyM Pillar IV: Liver Function Diagnostics (LiSyM-LiFuDi), Model Guided Pharmacotherapy In Chronic Liver Disease (LiSyM-MGP), Molecular Steatosis - Imaging & Modeling (LiSyM-MSIM), The Hedgehog Signalling Pathway (LiSyM-JGMMS), Multi-Scale Models for Personalized Liver Function Tests (LiSyM-MM-PLF), LiSyM PALs, Project Management PTJ, LiSyM network, LiSyM Scientific Leadership Team (LiSyM-LT)
Web page: https://www.lisym.org/
C-TIP-HCC- Mechanism-based Multiscale Model to Dissect the Tipping Point from Liver Cirrhosis to Hepatocellular Carcinoma
The ultimate goal of the C-TIP-HCC is a „mechanistic multiscale model to describe dynamic changes in regenerative nodes across a tipping point (TIP) towards development in patients with cirrhosis to facilitate early monitoring and intervention“ and facilitate intervention“. To achieve this, we will conduct in-depth studies on cirrhotic regenerative nodes.
Programme: LiSyM-Krebs - Systemmedizinisches Forschungsnetz zur Früherkennung und Prävention von Leberkrebs
Public web page: Not specified
Organisms: Homo sapiens, Mus musculus
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
Forschungsnetzwerk zur Früherkennung und Prävention- LiSyM-Krebs
Ein Netzwerk von Klinikern, Wissenschaftlern und Datenmanagern hat sich zur Aufgabe gemacht, Methoden zu entwickeln, um Patienten mit einem hohen Risiko für ein Leberkarzinom frühzeitig, in Vorstadien der Tumorentwicklung, identifizieren zu können. Gemeinsam bilden sie das „Systemmedizinische Forschungsnetzwerk zur Früherkennung und Prävention von Leberkrebs“, LiSym-Krebs, das vom Bundesministerium für Bildung und Forschung ...
Programme: LiSyM-Krebs - Systemmedizinisches Forschungsnetz zur Früherkennung und Prävention von Leberkrebs
Public web page: Not specified
Organisms: Homo sapiens, Mus musculus, Rattus norvegicus, Rattus rattus
This comprises the whole LiSyM network
Programme: LiSyM: Liver Systems Medicine
Public web page: http://www.lisym.org
Start date: 1st Jan 2016
Organisms: Rattus norvegicus, Rattus rattus, Mus musculus, Homo sapiens
In one in five people with NAFLD, the functioning liver cells, the hepatocytes, are replaced by connective tissue. Eventually this fibrosis becomes irreversible. In this state the liver is like a ‘scar that never heals’. Through it, the liver loses many of its vital functions. LiSyM-Pillar II wants to know more about which factors promote fibrosis and the conditions under which fibrosis becomes irreversible How can fibrosis be diagnosed as early as possible? Researchers in the pillar are also ...
Programme: LiSyM: Liver Systems Medicine
Public web page: http://www.lisym.org/our-work/pillar-research
Start date: 1st Jan 2016
Organisms: Mus musculus, Rattus rattus, Rattus norvegicus, Homo sapiens
Country: Germany
City: 79104 Freiburg im Breisgau
Upon stimulation of cells with transforming growth factorb(TGF-b),Smad proteins form trimeric complexes and activate a broad spectrum of target genes. It remains unresolved which of the possible Smad complexes are formed in cellular contexts and how these contribute to gene expression. Combining quantitative mass spectrometry with a computational selection strategy, we investigate Smad complexes in the mouse hepatoma cell line Hepa1-6.
Submitter: Olga Krebs
Studies: Study about Smad complexes in liver-derived cells
Assays: Modelling asssay II Lucarelli paper, exp assay I Lucarelli paper
Snapshots: No snapshots
In this study we identify most relevant Smad complexes in liver-derived cells, the contribution of the Smad complexes on target gene expression, and the role of Smad abundance and Smad2 phosphorylation in hepatocellular carcinoma
Submitter: Olga Krebs
Investigation: Investigation of the Smad Protein Complex Forma...
Assays: Modelling asssay II Lucarelli paper, exp assay I Lucarelli paper
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
Taken from https://github.com/Benchmarking-Initiative/Benchmark-Models See the github repository for license Import and execute the model in d2d
Creator: Jens Timmer
Submitter: Daniel Lill
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Taken from https://github.com/Benchmarking-Initiative/Benchmark-Models License according to the github repository's license Import and execute with d2d
Creators: Jens Timmer, Lorenza D'Alessandro, S.Sobotta, A. Raue, J. Vanlier
Submitter: Daniel Lill
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
All authors
Abstract (Expand)
Authors: Sebastian Burbano De Lara, Svenja Kemmer, Ina Biermayer, Svenja Feiler, Artyom Vlasov, Lorenza A D’Alessandro, Barbara Helm, Christina Mölders, Yannik Dieter, Ahmed Ghallab, Jan G Hengstler, Christiane Körner, Madlen Matz-Soja, Christina Götz, Georg Damm, Katrin Hoffmann, Daniel Seehofer, Thomas Berg, Marcel Schilling, Jens Timmer, Ursula Klingmüller
Date Published: 12th Jan 2024
Publication Type: Journal
DOI: 10.1038/s44320-023-00007-4
Citation: Mol Syst Biol
Abstract (Expand)
Authors: Sebastian Burbano De Lara, Svenja Kemmer, Ina Biermayer, Svenja Feiler, Artyom Vlasov, Lorenza D'Alessandro, Barbara Helm, Yannik Dieter, Ahmed Ghallab, Jan Hengstler, Professor Dr. med. Katrin Hoffmann, Marcel Schilling, Jens Timmer, Ursula Klingmüller
Date Published: 4th Jul 2023
Publication Type: Journal
DOI: 10.1101/2023.07.04.547655
Citation: biorxiv;2023.07.04.547655v1,[Preprint]
Abstract (Expand)
Authors: Simon Heming, Pauline Hansen, Artyom Vlasov, Florian Schwörer, Stephen Schaumann, Paulina Frolovaitė, Wolf-Dieter Lehmann, Jens Timmer, Marcel Schilling, Barbara Helm, Ursula Klingmüller
Date Published: 2022
Publication Type: Journal
Citation: Bioinformatics Advances 2(1),vbac004
Abstract (Expand)
Authors: L. Adlung, P. Stapor, C. Tonsing, L. Schmiester, L. E. Schwarzmuller, L. Postawa, D. Wang, J. Timmer, U. Klingmuller, J. Hasenauer, M. Schilling
Date Published: 10th Aug 2021
Publication Type: Journal
PubMed ID: 34380040
Citation: Cell Rep. 2021 Aug 10;36(6):109507. doi: 10.1016/j.celrep.2021.109507.
Abstract
Authors: Leonard Schmiester, Yannik Schälte, Frank T. Bergmann, Tacio Camba, Erika Dudkin, Janine Egert, Fabian Fröhlich, Lara Fuhrmann, Adrian L. Hauber, Svenja Kemmer, Polina Lakrisenko, Carolin Loos, Simon Merkt, Wolfgang Müller, Dilan Pathirana, Elba Raimúndez, Lukas Refisch, Marcus Rosenblatt, Paul L. Stapor, Philipp Städter, Dantong Wang, Franz-Georg Wieland, Julio R. Banga, Jens Timmer, Alejandro F. Villaverde, Sven Sahle, Clemens Kreutz, Jan Hasenauer, Daniel Weindl
Date Published: 26th Jan 2021
Publication Type: Journal
DOI: 10.1371/journal.pcbi.1008646
Citation: PLoS Comput Biol 17(1):e1008646
Jamboree presentation
Creators: Daniel Lill, Viktor Makarenko, Ursula Klingmüller, Jens Timmer
Submitter: Daniel Lill