Please note: This page is hosted by the e-Research Group at the University of Queensland, one of the collaborators on this project.
The official BioMANTA site can be found at biomanta.org.
The BioMANTA project is a two-year (2007 - 2008) scientific research collaboration funded by Pfizer Inc,. between
- The Computational Sciences Center of Emphasis, Pfizer Global Research and Development,
Pfizer Inc., Cambridge, Massachusetts, USA;
- The Institute for Molecular Bioscience (IMB) at the University of Queensland); and
- The School of Information Technology and Electronic Engineering (ITEE) at the University
The BioMANTA project focusses on the computational modeling and analysis, primarily using semantic web technologies, of large-scale protein-protein
interaction and compound activity networks across a wide variety of species. A range of information such as kinetic activity, tissue expression,
sub-cellular localisation and disease state attributes is included in the resulting data model.
Protein-protein interaction (PPI) data hold tremendous promise for a number of aspects of the drug discovery and development process. Impacts are
possible in areas as diverse as target identification, biomarker discovery, mechanistic modeling of toxicity and large-scale 'omics data analysis.
However, research into the collection, modeling and analysis of PPI data is not yet mature, and there is still much to be done in order to bring
capabilities in the integration, manipulation and analysis of PPI data to maturity.
Semantic web technologies allow for flexible data integration, inherent inferencing capabilities and advanced machine learning methods. Hence, the
BioMANTA project aims to bring together these areas through the modeling of PPI data in a semantic web framework, using technologies such as RDF
and OWL, and then to apply in silico and experimental analysis methods to analyze aspects of the BioMANTA data model.
Hypothetical user interface for the BioMANTA data models, showing how a user could query protein-protein interaction data, which can be determined through semantic pathway inferencing.
Specific goals of the BioMANTA project include:
- Identification of public data sources available for integration into BioMANTA;
- RDF modeling of multiple public biological and chemical data sources;
- Dissemination of project information and data via the BioMANTA website;
- Development of methods for semantic pathway inferencing;
- Development of methods for visualisation of BioMANTA dat;a
- Application of the BioMANTA framework to modeling of specific kinasep pathways;
- Mathematical modeling of biological and chemical network data;
- Assessment of information content in networks;
- Ranking of interactions across species;
- Development of methods for pathway analysis of 'omics data.