OMICS 4.0
The major aim of the OMICS 4.0 project is to integrate existing metabolomics, proteomics, transcriptomics and genomics activities at the Campus Technopol Tulln. The project intends to establish a bioinformatics platform to promote collaborations among the various research groups being active in the respecive OMICS disciplines.
Virtual meetings
(March-July 2020)
The project work continued during the COVID-10 pandemic as bioinformatics work can be carried out remotely and via virtual meetings.
11th of April 2019
On the 11th of April 2019 Justin JJ. van der Hooft has been invided to present his ground-breaking work on substructure motif discovery using the developed MS2LDA platform. For further details see the official announcement.
12th of December 2018
On the 12th December 2018 our kickoff-meeting will take place at the UFT-Tulln.
1st of June 2023
On the 1st June 2023 the Data 4 Omics Symposium took place. Please find further information about the conference organized in the course of the OMICS4.0 project at metabolomics-ifa.boku.ac.at/Data4Omics_Symposium.
October 2018
The OMICS 4.0 project is a dedicated bioinformatics project involving 4 research groups situated at the University of Natural Resources, Vienna (Location IFA-Tulln), the University of Applied Sciences, FH Wiener Neustadt, Campus Tulln and the Austrian Institute of Technology, Campus UFT Tulln.
To be able to meet the challenges of the fast developing OMICS-technologies and to ensure adequate handling of the associated, steadily increasing amount of data, novel algorithms and bioinformatics tools are indispensable.
The major aim of the OMICS 4.0 project is to integrate existing metabolomics, proteomics, transcriptomics and genomics activities at the Campus Technopol Tulln. The project intends to establish a bioinformatics platform to promote collaborations among the various research groups being active in the respective OMICS disciplines.
The project is structured in four scientific modules (see below), all of which intend to develop novel, customized bioinformatics tools for processing, statistical evaluation, visualization and interpretation of analytical raw data. To maximize the benefit of the tools to be developed, each of the bioinformatics research fellows (PhD students and Postdocs) will be fully integrated into a specific ongoing life science project, addressing defined biological research questions. For each of these associated projects, defined user-friendly software packages shall be developed.
The OMICS 4.0 project started on the 1st of October 2018 and will last for four years
Biomarker zur Darmgesundheit von Nutztieren
The associated module of this project performs research in the framework of a Christian Doppler laboratory and deals with gut health in cows and pigs. One part of that is the search for novel biomarkers indicating health or disease in cows and pigs. For this, targeted and untargeted metabolomics approaches will be used.
More information about the CD Lab can be found here.
University for Natural Resources and Life Sciences, Vienna (BOKU)
A pleiotropic regulator of secondary metabolism
The associated module of this project will perform untargeted metabolomics in order to study filamentous fungi with a special focus on the fungus Trichoderma reseei that is an important strain used in many biotechnological applications and a potent producer of many different secondary metabolites used in various applications.
More information about the project can be found here.
University for Natural Resources and Life Sciences, Vienna (BOKU)
Wheat plants have a large metabolic inventory and many of these metabolites are believed to be involved in the fight against the pathogenic fungi Fusarium graminearum, which casues the devastating disease Fusarium head blight. The PhD in this module will integrate transcriptomics and metabolomics datasets to investigate these metabolic defense strategies.
University for Applied Sciences,
FH Wiener Neustadt, Campus Tulln
Modern omcis experiments produce a vast number of data and the information steadily grows. Unfortunately, our understanding of these datasets does not grow at nearly the same rate. This module will try to improve the automated analysis of transcriptomics datasets as well as metabolomic datasets.
Austrian Institute of Technology, Campus UFT Tulln
Gefördert durch das Land Niederösterreich.
Funding for this project has been kindly provided by the Office of the Provincial Government of Lower Austria.
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