Finished Projects geneXplain

Finished Projects

MIMOmics

Methods for Integrated analysis of Multiple Omics datasets

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A collaborative project funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 305280, research area FP7-HEALTH-2012-INNOVATION-1, topic HEALTH.2012.2.1.1-3: Statistical methods for collection and analysis of –omics data.

MIMOmics aims at developing robust and efficient statistical methods for the integrated analysis of metabolomics, glycomics, proteomic and genomic datasets in large studies.

It was triggered by the repeated observation that the existing methodology for analyzing huge data sets does not match by far the complexity of the biological problem addressed. Expensive and complex data are gathered and being analysed in a rather simple way, thereby missing the opportunity to uncover combinations of predictive and meaningful profiles among the different kinds of omics data. Novel methods should integrate multilevel omics data to bring biological understanding to the next level. Due to the high dimensionality of the datasets the multiple testing burden becomes heavier and consequently the false positive and negative rates increase. Super-meta methods combining multilevel data across populations need to be developed.

Due to the high dimensionality of the datasets the multiple testing burden becomes heavier and consequently the false positive and negative rates increase. Super-meta methods combining multilevel data across populations need to be developed.

GeneXPlain will provide the consortium with the geneXplain platform for data handling and analysis in order to integrate databases of molecular networks with state of the art bioinformatics and systems biology tools. This way, we will support the analysis of pre-existing omics data and apply them for building efficient systems biology models. We will also work on integrating analytical tools developed within the MIMOmics project with already existing systems biology data and knowledge. GeneXplain will be strongly involved in the project’s dissemination activities, thereby particularly considering potential partners from industries.

SysmedIBD

SysmedIBD– Systems medicine of chronic inflammatory bowel disease

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A collaborative project funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 305564, research area FP7-HEALTH-2012-INNOVATION-1, topic HEALTH.2012.2.1.2-2: Systems medicine: Applying systems biology approaches for understanding multifactorial human diseases and their comorbidities.

By applying a systems-biological approach, the project SysmedIBD aims at revealing oscillating biological processes associated with the inflammatory bowel disease (IBD). IBD is a major health problem with severe co-morbidities, requiring life-long treatment. Oscillating processes such as circadian rhythms are well studied and modeled in a number of systems. In the case of IBD as in other inflammatory processes, one particular transcription factor (NF-kappaB) is known to play a key role. Recently, NF-kappaB-associated processes have also been shown to be oscillating. In this project, we will study NF-kappaB oscillation in chronic inflammatory bowel diseases in animal models and patient cohorts with immunosuppressive treatments and controls. The aim is to build an experimentally validated mathematical model of the NF-kappaB oscillation in the gut tissue.

The validated model will enable searching for critical molecular components of the NF-kappaB oscillation and to assess their relevance for the disease in patients.

Gaining control of the oscillation of biological pathways may provide new possibilities to influence biological processes like inflammation. Hence, we will search (assisted by the models and databases developed) for small molecules interfering with the NF-kappaB oscillation and validate selected candidates in experimental systems. Owing to its highly focused system biological approach, the project will generate substantial insights into key mechanisms underlying IBD.

GeneXplain will be involved in the dynamic simulation of the oscillating processed described above, and in the identification of suitable targets and drug candidates, which will then be experimentally validated by the partners.

RESOLVE

A systems biology approach to RESOLVE the molecular pathology of two hallmarks of patients with metabolic syndrome and its co-morbidities; hypertriglyceridemia and low HDL-cholesterol

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A collaborative project funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 305707, research area FP7-HEALTH-2012-INNOVATION-1, topic HEALTH.2012.2.1.2-2: Systems medicine: Applying systems biology approaches for understanding multifactorial human diseases and their comorbidities

Through combining basic pre-clinical and clinical research, network analysis and computational modelling, RESOLVE aims at resolving the disturbed dynamics and mechanisms underlying the high triglyceride (HTG) and low high-density lipoprotein cholesterol (HDL-C) phenotype and insulin resistance in patients with metabolic syndrome (MetS) and its associated co-morbidities (cardiovascular disease, CVD; type 2 diabetes, T2DM; non-alcoholic fatty liver disease, NAFLD). RESOLVE will deliver on 6 specific objectives:

build a computational model for analyzing the kinetics of plasma lipids, lipoproteins and their interactions with glucose metabolism;
apply the iterative systems biology cycle for calibrating, validating and improving the computational model in dedicated studies in mice;

build, calibrate and validate the computational model for use in humans;
analyze – based on model and experimental data – which processes in the murine metabolic network regulatethe physiological response to perturbations in lipid, lipoprotein and glucose metabolism and how these interact;
analyze – based on model and experimental data – which processes in the human metabolic network regulatethe physiological response to perturbations in lipid, lipoprotein and glucose metabolism and how these interact;
use the human model to identify network-based drug targets aimed at restoring the metabolic dyslipidemia and glycemic control in patients with MetS and associated comorbidities.

The 60-months project RESOLVE will result into a novel strategy for development of therapeutic strategies for MetS patients with T2DM, NAFLD or CVD.

GeneXplain’s role is to contribute to the general IT infrastructure of the project, to use the company’s technology platform for providing a database of the project-specific data, and to help with training courses for the data management.

SYSCOL

Systems Biology of Colorectal Cancer

A collaborative project funded by the European Union Seventh Framework Programme ( FP7/2007-2013 ) under grant agreement no. 258236, research area HEALTH.2010.2.1.2-1, Tackling Human Diseases through Systems Biology Approaches.

Coordinator:
The project is coordinated by Prof. Jussi Taipale, Karolinska Institute, Uppsala, Sweden. The 11 participants of the consortium are from 8 European countries, from Israel and the United States.

Contract period: January 1st, 2011 – December 31st, 2015

Contract no. 258236.

Summary:
SYSCOL is a systems biological project that aims at developing a quantitative and comprehensive model of colorectal tumorigenesis, one of the most common cancers in both males and females.

GeneXPlain contributes to the project by developing an integrative tool platform for bioinformatic and systems biological software and databases.

Further information:

Homepage of SYSCOL.

Press release of the Karolinska Institute
Project description on the CORDIS server of the European Commission

Jussi Taipale’s collection of Positional Weight Matrices, the most comprehensive experimental set available to date (Jolma et al., Cell 153: 327-338, 2013; PMID 23332764), has been consistently linked to E. Wingender’s transcription factor classification.

Publications:

Wingender, E., Schoeps, T., Haubrock, M., Dönitz, J. (2015) TFClass: a classification of human transcription factors and their rodent orthologs. Nucleic Acids Res., in press. doi: 10.1093/nar/gku1064. Link

Wingender, E. (2013) Criteria for an updated classification of human transcription factor DNA-binding domains. J. Bioinform. Comput. Biol. 11, 1340007. doi: 10.1142/S0219720013400076. Link

Wingender, E., Schoeps, T., Dönitz, J. (2013) TFClass: An expandable hierarchical classification of human transcription factors. Nucleic Acids Res. 41, D165-D170. doi: 10.1093/nar/gks1123. Link

GERONTOSHIELD

GERONTO^SHIELD – Systems biology-driven approach to unravel and revert the mechanisms responsible for poor immune responses in the elderly

A collaborative project funded by the German Federal Ministry of Education and Research (BMBF) in the funding program “Systems Biology for Health in the Old Age – GerontoSys2”

Coordinator:
The project is coordinated by Prof. Dr. Carlos Guzmán, Helmholtz Centre for Infection Research (HZI) in Braunschweig, Germany. The 6 participants of the consortium are from Braunschweig, Jena, Martinsried, Regensburg, Tübingen, and Wolfenbüttel.

Contract period: February 1st, 2011 – January 31st, 2014
Grant no.: FKZ0315890B
Summary:

The strategic objective of the GERONTOSHIELD project is to draw on a Systems Biology-driven approach to understand the molecular processes affected during immunosenescence, in order to derive (i) global mathematical models describing the involved processes, (ii) a holistic model for flu infections in young and elderly, and (iii) strategies to overcome these processes to establish immune interventions tailored for the elderly.

Further information:
Homepage of GERONTOSHIELD
Press release of the Helmholtz Centre for Infection Research (HZI; in German)
Press release of the Helmholtz Centre for Infection Research (HZI; in English)

Publications:
Wingender, E. (2013) Criteria for an updated classification of human transcription factor DNA-binding domains. J. Bioinform. Comput. Biol. 11, 1340007. doi: 10.1142/S0219720013400076. Link
Wingender, E., Schoeps, T., Dönitz, J. (2013) TFClass: An expandable hierarchical classification of human transcription factors. Nucleic Acids Res. 41, D165-D170. doi: 10.1093/nar/gks1123. Link

TEMPUS

TEMPUS project “Rehaut”

A collaborative educational & training project financially supported by TEMPUS program of the European Union, phase TEMPUS IV, under grant agreement no. 511426-TEMPUS-1-2010-1-RU-TEMPUS-JPCR.

Coordinator:
The project is coordinated by Prof. Alexander Kuznetsov, D. Mendeleyev University of Chemical Technology of Russia, Moscow. The participants of the consortium are from 3 EU member states, from Russia and Belorus.

Contract period: October 15th, 2010 – October 14th, 2013

Summary:
The project aims at harmonizing, standardizing and developing further the European BSc and MSc biotechnology curricula and their applicability to biotechnology education in Belorus and Russia. It is geneXplain’s contribution to reinforce the industrial view in this project, in particular with regard to the inclusion of the methods of computational biology.

Further information:News about the project from the National TEMPUS Office of Belorus.
Rehaut Tempus project page (in Russian)

EPIMETAB

EPIMETAB Epigenetic mechanisms underlying predisposition to metabolic syndrome-associated diseases

A collaborative project funded by the German Federal Ministry of Education and Research (BMBF) in a Joint Transnational Call 2011 for “Integrated Research on Genomics and Pathophysiology of the Metabolic Syndrome and the Diseases arising from it”
Coordinator:
The project is coordinated by Prof. Dr. Pierre Fafournoux, Institut National de la Recherche Agronomique in Saint Genès Champanelle, France. The 4 participants of the consortium are from France (Saint Genès Champanelle and Paris), Spain (Barcelona), and Germany (Wolfenbüttel).
Contract period: April 1st, 2012 – March 31st, 2015
Summary:
The project aims at gaining a better insight on the etiology of different disease conditions such as obesity or type-2 diabetes by investigating the intertwining of genetic, epigenetic and environmental factors. This innovative project is expected to pave the way to new preventive and therapeutic approaches at the individual level and for ameliorating the quality of life at the general population level.
GeneXplain contributes to the project its expertise in promoter analysis and its platform, which will be adapted to the specific needs of the project partners. At the end, a novel integrative view on the regulatory network comprising genetic and epigenetics influences will be provided.

Further information: Project summary (pdf; 8kB)

ExITox

ExITox – Explain Inhalation Toxicity

A collaborative project funded by the German Federal Ministry of Education and Research (BMBF) in the funding program “e:ToP – Innovative Toxikologie zur Reduzierung von Tierversuchen”

Coordinator:
The project was coordinated by Dr. Sylvia Escher, Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM) in Hannover, Germany. The 6 participants of the consortium are from Hannover, Freiburg, Göttingen, and Wolfenbüttel.

Contract period: November 1st, 2013 – October 31st, 2015, extended until January 31st, 2016
Grant no.: 031 A269 D

Summary:
This project aims at developing an integrated testing strategy (ITS) for the human health risk assessment of repeated dose toxicity after inhalation exposure for the replacement of de novo animal testing. In the pilot phase chemicals with different mode of action will be selected and tested with human precision cut lung slices (PCLS) and human pulmonary cell cultures in order to identify route specific biomarkers. Genome wide transcriptome analyses will be conducted in these models and evaluated using bioinformatics methods. These results will be complemented with data mining results and QSAR predictions. Further, structurally related chemicals will be tested in addition to investigate the possibility of the test system to support read across. The outcome of this pilot project will be a proposal for an integrated testing strategy for respiratory toxicity. Further validation e.g. testing of a broader spectrum of chemicals is foreseen in a follow up project. The proposed ITS, the developed methodologies on data sharing and data integration are not limited to the evaluation of transcriptome data but allow to integrate proteome and metabolome data in a follow up project.
It is geneXplain’s task to analyze transcriptome data of the partners and contribute to the specification of new biomarkers.

Further information:
Homepage of the project at Fraunhofer ITEM
Fraunhofer-Datenbank RepDose
Research Database at Albert Ludwigs University Freiburg (in German)

Publications:
Koschmann, J., Bhar, A., Stegmaier,P., Kel, A. E. and Wingender, E. (2015) “Upstream Analysis”: An integrated promoter-pathway analysis approach to causal interpretation of microarray data. Microarrays 4, 270-286. doi:10.3390/microarrays4020270. Link

Niehof, M., Hildebrandt, T., Danov, O., Arndt, K., Koschmann, J., Dahlmann, F., Hansen, T. and Sewald, K. (2017) RNA isolation from precision-cut lung slices (PCLS) from different species. BMC Res. Notes 10, 121. doi: 10.1186/s13104-017-2447-6. Link

The project continues with ExITox-II.

Mediomics

Mediomics – Systems biology modeling of diseases through integration of multiple “-omics” data

A collaborative Russian-German project funded by the German Federal Ministry of Education and Research (BMBF) and the Russian Fund for Assistance to Small Innovative Enterprises (FASIE).

Coordinator:
Dr. Alexander Kel, geneXplain GmbH. The 3 partners are University Regensburg and University Medical Center Göttingen from Germany and biosoft.ru from Russia.

Funding period: December 1st, 2013 – August 31st, 2016 (with extension)

Summary:
The main goal of the project is to push ahead the idea of a systems-biological software platform that integrates different high-throughput (‘omics’) data to generate models for certain chronic diseases. A particular focus of the project will be given onto the inclusion of gene regulatory processes into the modeling, which is still largely neglected by present systems biological modeling approaches.

Further information:
Project page at the University Medical Center Göttingen