Sophia Müller-Dott

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About Sophia Müller-Dott:

No description specified

SEEK ID: https://seek.lisym.org/people/184

Location: Germany

ORCID: https://orcid.org/0000-0002-9710-1865

Joined: 28th Jun 2023

Expertise: Not specified

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LiSyM-Krebs - Systemmedizinisches Forschungsnetz zur Früherkennung und Prävention von Leberkrebs

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

LiSyM: Liver Systems Medicine

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/

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Forschungsnetzwerk LiSyM-Krebs

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

C-TIP-HCC network

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

LiSyM network

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

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Heidelberg University - Institute for Computational Biomedicine

Country: Germany

City: Heidelberg

Web page: Not specified

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Hepatocytes reprogram liver macrophages involving control of TGF-β activation, influencing liver regeneration and injury.

Forschungsnetzwerk LiSyM-Krebs, C-TIP-HCC network

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Macrophages play an important role in maintaining liver homeostasis and regeneration. Here we investigate how different macrophage populations of the liver differ in terms of their activation state and which other liver cell populations may play a role in regulating the same.

Submitter: Stephanie Wolf

Studies: Study changes in gene expression and in the activation state of macropha...

Assays: Hepatocytes induces properties of wound healing type and regulatory macr..., Transcriptomics : RNA Microarray, Transcriptomics: RNA-seq of coding RNA from single cells

Snapshots: No snapshots

Created: 2nd Aug 2023 at 08:52, Last updated: 6th May 2024 at 07:40

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C-TIP-HCC network

No description specified

Creator: Sophia Müller-Dott

Submitter: Sophia Müller-Dott

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

External Link

Created: 11th Dec 2024 at 13:25

Public data stored in Zenodo

C-TIP-HCC network

No description specified

Creator: Sophia Müller-Dott

Submitter: Sophia Müller-Dott

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Created: 11th Dec 2024 at 13:25

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Comprehensive evaluation of phosphoproteomic-based kinase activity inference (preprint)

Forschungsnetzwerk LiSyM-Krebs, C-TIP-HCC network

Abstract (Expand)

Kinases play a central role in regulating cellular processes, making their study essential for understanding cellular function and disease mechanisms. To investigate the regulatory state of a kinase, … numerous methods have been, and continue to be, developed to infer kinase activities from phosphoproteomics data. These methods usually rely on a set of kinase targets collected from various kinase-substrate libraries. However, only a small percentage of measured phosphorylation sites can usually be attributed to an upstream kinase in these libraries, limiting the scope of kinase activity inference. In addition, the inferred activities from different methods can vary making it crucial to evaluate them for accurate interpretation. Here, we present a comprehensive evaluation of kinase activity inference methods using multiple kinase-substrate libraries combined with different inference algorithms. Additionally, we try to overcome the coverage limitations for measured targets in kinase substrate libraries by adding predicted kinase-substrate interactions for activity inference. For the evaluation, in addition to classical cell-based perturbation experiments, we introduce a tumor-based benchmarking approach that utilizes multi-omics data to identify highly active or inactive kinases per tumor type. We show that while most computational algorithms perform comparably regardless of their complexity, the choice of kinase-substrate library can highly impact the inferred kinase activities. Hereby, manually curated libraries, particularly PhosphoSitePlus, demonstrate superior performance in recapitulating kinase activities from phosphoproteomics data. Additionally, in the tumor-based evaluation, adding predicted targets from NetworKIN further boosts the performance, while normalizing sites to host protein levels reduces kinase activity inference performance. We then showcase how kinase activity inference can help in characterizing the response to kinase inhibitors in different cell lines. Overall, the selection of reliable kinase activity inference methods is important in identifying deregulated kinases and novel drug targets. Finally, to facilitate the evaluation of novel methods in the future, we provide both benchmarking approaches in the R package benchmarKIN.

Authors: Sophia Müller-Dott, Eric J. Jaehnig, Khoi Pham Munchic, Wen Jiang, Tomer M. Yaron-Barir, Sara R. Savage, Martin Garrido-Rodriguez, Jared L. Johnson, Alessandro Lussana, Evangelia Petsalaki, Jonathan T. Lei, Aurélien Dugourd, Karsten Krug, Lewis C. Cantley, D. R. Mani, Bing Zhang, Julio Saez-Rodriguez

Date Published: 2nd Jul 2024

Publication Type: Journal

DOI: 10.1101/2024.06.27.601117

Citation: biorxiv;2024.06.27.601117v1,[Preprint]

Created: 5th Jul 2024 at 07:42

Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities

Forschungsnetzwerk LiSyM-Krebs, C-TIP-HCC network

Abstract (Expand)

Abstract Gene regulation plays a critical role in the cellular processes that underlie human health and disease. The regulatory relationship between transcription factors (TFs), key regulators of gene …

Authors: Sophia Müller-Dott, Eirini Tsirvouli, Miguel Vazquez, Ricardo O Ramirez Flores, Pau Badia-i-Mompel, Robin Fallegger, Dénes Türei, Astrid Lægreid, Julio Saez-Rodriguez

Date Published: 10th Nov 2023

Publication Type: Journal

DOI: 10.1093/nar/gkad841

Citation: Nucleic Acids Research 51(20):10934-10949

Created: 27th Nov 2023 at 13:25, Last updated: 8th Mar 2024 at 07:44

Gene regulatory network inference in the era of single-cell multi-omics.

LiSyM network, Forschungsnetzwerk LiSyM-Krebs, C-TIP-HCC network

Abstract (Expand)

The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand …

Authors: P. Badia-I-Mompel, L. Wessels, S. Muller-Dott, R. Trimbour, R. O. Ramirez Flores, R. Argelaguet, J. Saez-Rodriguez

Date Published: 26th Jun 2023

Publication Type: Journal

PubMed ID: 37365273

Citation: Nat Rev Genet. 2023 Jun 26. doi: 10.1038/s41576-023-00618-5.

Created: 28th Jun 2023 at 14:35, Last updated: 8th Mar 2024 at 07:44

Hepatocytes reprogram liver macrophages involving control of TGF-β activation, influencing liver regeneration and injury

LiSyM Pillar II: Chronic Liver Disease Progression (LiSyM-DP), LiSyM Pillar III: Regeneration and Repair in Acute-on-Chronic Liver Failure (LiSyM-ACLF), Forschungsnetzwerk LiSyM-Krebs, C-TIP-HCC network

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Abstract (Expand)

Background: Macrophages play an important role in maintaining liver homeostasis and regeneration. However, it is not clear to what extent the different macrophage populations of the liver differ in …

Authors: Stephanie D. Wolf, Christian Ehlting, Sophia Müller-Dott, Gereon Poschmann, Patrick Petzsch, Tobias Lautwein, Sai Wang, Barbara Helm, Marcel Schilling, Julio Saez-Rodriguez, Mihael Vucur, Kai Stühler, Karl Köhrer, Frank Tacke, Steven Dooley, Ursula Klingmüller, Tom Luedde, Johannes G. Bode

Date Published: 2023

Publication Type: Journal

DOI: 10.1097/HC9.0000000000000208

Citation: Hepatology Communications 7(8)

Created: 27th Jul 2023 at 11:22, Last updated: 8th Mar 2024 at 07:44

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