Systems Biology BioSignature Discovery Services

Systems Biology Modeling service models biological responses to diseases and treatments for biological discovery and for pre-symptomatic diagnostics. Models are custom-built based on your investigative objectives.

The models can be as simple as a signaling pathway or as complex as hierarchical models involving multiple pathways and multiple tissues. Proprietary dynamic Bayesian networks are used to structure, train, and refine models. Previous comparative analyses, such as those done during Transcriptomic and Proteomic Analyses, identify pathway mechanisms which are used to construct Systems Biology models. The models integrate prior knowledge such as known genetic relations, and can include important elements such as host phenotypes, physiological responses, and temporal dependences.

Gene Regulatory Structure Learning Services

An alternate and newly prototyped system model learning approach has been recently developed by Seralogix. Our algorithmic innovation incorporates biological prior knowledge and multi-perturbation data, such as gene knockdown or multi-conditional experiments, with our dynamic Bayesian technology for enabling a network learning approach that is not limited to prior pathway networks. This service is ideal for large scale gene knockout time-series experiments in which the discovery of gene relationships and biological process association is the experimental objective. The approach is described briefly in the systems biology computational approach.