Projects with Biomax

Find out how our customization projects have helped our customers reach their goals faster.

• Integrative Genomics and Chronic Disease Phenotypes: modelling and simulation tools for clinicians
  BioBridge is a consortium dedicated to use the omics revolution data explosion to improve the mechanistic understanding of of complex chronic disorders. To this end BioBridge not only generates clinical and experimental data, but also a Systems Biology infrastructure, which provides a tool for data integration and simultaneous analysis of different levels of information. Biomax is a central partner for BioBridge and provides the data integration and knowledge management infrastructure.
• Building a comprehensive cancer gene index
  Sophic and Biomax have teamed with the National Cancer Institute (NCI) to develop the "Cancer Gene Index," a single source to help cancer researchers accelerate the search for cancer cures.
• Bioinformatics data integration
  The goal of the "SMP Bioinformatics — Data Integration" subproject is to provide a bioinformatics infrastructure that creates a homogeneous retrieval environment for accessing the heterogeneous and distributed data sets of the NGFN2 network as well as public data.
• Gene expression simulation
  Siemens AG Corporate Technology and Biomax have formed a strategic alliance in the area of gene expression modeling and simulation. Complementary and unique technologies are combined to simulate gene expression data in silico.
• Enhancing translational efficiency
  Results from a large-scale expression experiment were used to develop a method for predicting and improving translation efficiency. The developed software, ProteoExpert, is available on the Internet and allows individual, rational design of coding regions for optimal expression in the Rapid Translation System from Roche Diagnostics.
• Functional analysis of mammalian genomes
  Biomax contributes to a consortium dedicated to the functional analysis of mammalian genomes (BFAM). The Biomax infrastructure includes methods and content for analysis of gene expression and metabolic pathways. An annotation system allows interrelated data of different types to be associated and used for identifying relevant information.