Our team has implemented clinical genomics systems in private cloud infrastructure and has automated a clinical genomics pipeline through the enhancement, automation, and consolidation of existing bioinformatics tools. This reduced the number of people required to perform precision medicine work from 30 down to five. Additionally, by building rules engines that evaluate a large base of clinical evidence, we can help you overcome informatics barriers and integrate patient sequencing ordering and complex and customized informatics analyses of sequenced genes.

Translational Research

With our systems, we bridge that gap that can often exist between basic science and translational research technologies to streamline access to data while providing the necessary flexibility for complex analytics. Our solutions focus on identifier management and mapping, deidentification, federation data querying and data aggregation. We also can leverage a federated approach, where data resides in its native system, or a data warehouse approach where data is periodically imported into a system designed for translational needs.


Proteomic is a hallmark of big data work, and given the mass amounts of this type of information being collected, the ability to quickly and easily interpret it is essential. Using bioinformatic techniques, our team of hardware and software experts is able to work with any organization to address specific solutions to their unique problems so that they can make sense of their data in ways that are useful across a variety of health fields.

Gene Expression

Though gene expression is an established technology, implementing it today can still be a complicated process. Analyzing gene expression can be done using a number of techniques, and often there are considerable variables and biases to factor in. Our familiarity with this technology allows us to assist in the analytics process, regardless of whether you are doing RNA quantification or cDNA expression profiling. We further use our knowledge to provide solutions for the storage and integration of gene expression data as well.