Sylvie Schulze

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About Sylvie Schulze:

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SEEK ID: https://funginet.hki-jena.de/people/71

Location: Germany

ORCID: Not specified

Joined: 7th Mar 2016

Expertise: Gene Regulatory Network Inference

Tools: Not specified

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Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

The yeast Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of life-threatening invasive mycoses in Europe. Despite the increasing incidence of these infections, the current diagnosis is still difficult and often too late, and options for therapies are limited. Moreover, A. fumigatus and C. albicans have developed multiple sophisticated, specific and unique pathogenicity mechanisms. Many of these mechanisms are not well understood. Research on ...

Projects: FungiNet total, FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF, A1, A2, A3, A4 (E), A5, B1, B2, B3 (E), B4, C1, C2, C3, C4 (E), C5, C6 (E), Z2, Z1, B5, A6, A7, A8, C7

Web page: http://www.funginet.de/home.html

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B3 (E): inactive since 2018-06-07

Predictive modelling of host-fungal pathogen interactions by reconstruction of gene regulatory networks

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-b3.html

Organisms: Aspergillus fumigatus, Candida albicans

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Leibniz-Institute for Natural Product Research and Infection Biology Hans Knöll Institute (HKI)

Country: Germany

City: 07745 Jena

Web page: http://www.hki-jena.de

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LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

INF

Abstract (Expand)

Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present … large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naive Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.

Authors: R. Magnusson, G. P. Mariotti, M. Kopsen, W. Lovfors, D. R. Gawel, R. Jornsten, J. Linde, T. E. M. Nordling, E. Nyman, S. Schulze, C. E. Nestor, H. Zhang, G. Cedersund, M. Benson, A. Tjarnberg, M. Gustafsson

Date Published: 24th Jun 2017

Publication Type: Not specified

PubMed ID: 28640810

Citation: PLoS Comput Biol. 2017 Jun 22;13(6):e1005608. doi: 10.1371/journal.pcbi.1005608. eCollection 2017 Jun.

Created: 11th Feb 2021 at 09:44, Last updated: 17th Jan 2024 at 10:24

How to Predict Molecular Interactions between Species

FungiNet B - Bioinformatics projects, INF

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Organisms constantly interact with other species through physical contact which leads to changes on the molecular level, for example the transcriptome. These changes can be monitored for all genes, …

Authors: , J. Schleicher, ,

Date Published: 31st Mar 2016

Publication Type: Not specified

PubMed ID: 27065992

Citation:

Created: 29th Apr 2016 at 11:33, Last updated: 17th Jan 2024 at 10:24

Candida albicans infection leads to barrier breakdown and a MAPK/NF-kappaB mediated stress response in the intestinal epithelial cell line C2BBe1

FungiNet B - Bioinformatics projects, INF

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Intestinal epithelial cells (IEC) form a tight barrier to the gut lumen. Paracellular permeability of the intestinal barrier is regulated by tight junction proteins and can be modulated by microorganisms …

Authors: M. Bohringer, S. Pohlers, , , J. Piegsa, M. Weber, R. Martin, , , ,

Date Published: 12th Jan 2016

Publication Type: Not specified

PubMed ID: 26752615

Citation:

Created: 11th Mar 2016 at 08:44, Last updated: 17th Jan 2024 at 10:24

Data- and knowledge-based modeling of gene regulatory networks: an update

FungiNet B - Bioinformatics projects, INF, B3 (E)

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Abstract (Expand)

Gene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated network …

Authors: , , S. G. Henkel,

Date Published: 2nd Mar 2015

Publication Type: Not specified

PubMed ID: 27047314

Citation:

Created: 10th May 2016 at 08:31, Last updated: 17th Jan 2024 at 10:24

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