- Consulting on "design of experiments"
- Data importation for analysis: next generation RNA sequence reads, microarrays, etc.
- Experiment data management from multi-perturbation studies
- Annotation updating to latest reference genome
- Comprehensive analysis and modeling
- Knowledge curation for pathways, gene ontologies, interactions and more
- Client training on interpretation of results
- Client support
Gene expression analysis offers a model-based analysis of microarray or rnaSEQ, or mass spec data including classical statistical analyses. Because BioSignatureDS™ incorporates Bayesian network learning and modeling for its analysis of gene groups and single genes, sensitivity of detecting more subtle modulations in genes is possible. Our computational pipeline supports most microarray and sequencing platforms. Our integrated platform rapidly processes the raw sequencing reads into a complete and comprehensive analysis report.
Proteomics data can be integrated with transcriptomic data or analyzed by itself. Systems level analysis of your proteomics data provides the identification of pathways and biological processes altered in your single or multi-time point data sets. Learned from your data, our Dynamic Bayesian Network analysis methods identifies mechanistic proteins and transcription factors and their regulatory relationships to other proteins and genes.
DNA next gen sequencing data can be analyzed and mined for biologically relevant variants. Complex cross-comparative analyses can be conducted to identify and prioritize variants associated with a particular phenotype.
BioSignatureSB™ 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. All models can be visualized and interrogated through the AMVIZManager via the web.
Interactome analysis and modeling is the process of learning the interactions between pathogen and host during the course of infection that disrupt the host immune response. Through advanced computational methods of predicting points of interaction (i.e., protein-protein interactions) combined with prior biological knowledge coupled with the use of experimental data, the time-course mechanisms of interaction are predicted. Interaction learning can be done for bacterial, viral, or toxins. All interactome models can be visualized and interrogated through the AMVIZManager via the web. A complete system-level mechanistic understanding of disease pathogenesis and host response is created with the results used in the discovery of targets of interventions (drugs, diagnostic)
Seralogix can relieve our clients burden of managing vast amounts of multiple "OMIC" data types. We employ intelligent tools and database storage solutions specialized for the management and curation of our client's experimental data in a secure environment. Seralogix's Omic Data Management™ Services remove the tedious details of managing data, and tracking workflows; allowing scientists to concentrate on interpreting results and making discoveries.