Oliver Ruebenacker's vision is that software tools can automatically learn about biological pathways and networks and make precise prediction about the biological and medical fate of a person or another living being - in their normal state, or as a response to a disease, a drug or other types of intervention.
Sequencing the genome of a person or other organism is rapidely becoming faster and cheaper. The same is true for turning annotated genomes into biological pathways and reaction networks, which can be turned into mathematical models for computer simulations. We are beginning to learn how to predict the effect of a drug before actually applying it.
Oliver has been involved intensively with kinetic modeling during his work at the Virtual Cell. He had a significant contribution to the development of Biological Pathway Exchange (BioPAX), the de-facto standard for biological pathways, and has been elected BioPAX editor. Oliver has worked on theory and implementation of combining pathways in BioPAX with modeler's preferences to create VCell models and Systems Biology Markup Language (SBML) models. Oliver has been elected BioPAX editor and has developed a BioPAX extension called Systems Biology Pathway Exchange (SBPAX) to include quantitative data, which features Unit of Measurement Expressions (UOME) and links to systems biology vocabularies such as the Systems Biology Ontology (SBO). SBPAX is now implemented by two popular pathway databases with quantitative data and by the VCell.
Oliver has received his MS and PhD in Physics from the University of Massachusetts (UMass) at Amherst. His PhD research in statistical physics on Bose Gases in the Fluctuation Region involved computer simulations and finding universal properties across different types of systems to obtain predictions with unprecedented accuracy over a wide parameter range.
Oliver is the President and Founder of the Knowomics Bioinformatics Network, a collaboration of bioinformatics service providers who address the IT needs of biological and medical researchers and practitioners through consulting, training or through the development or setup of software tools.
Currently, Oliver is working on Flux Change Analysis, a novel powerful and flexible approach to use biological networks to analyze measurements that reveal differences between individuals. Flux Change Analysis is an approach that combines features of Flux Balance Analysis, kinetic modeling and statistical analysis into an algorithm to reduce and transform variables to construct hypotheses and calculate predictions.