Data Sciences & Computational Biology Unit (DSCB)

The biological sciences have experienced a profound transformation in the ability to generate data, moving from a time of relative data scarcity to one of great abundance.  The grand challenge now is to develop methods that can capitalize on this wealth of data to derive knowledge and insight about systems that was before unattainable.
The DSCB unit turns the rich sources of data generated by the operating divisions into actionable knowledge used to enable our Design-Build-Test-Learn™ development cycle.  This iterative approach aims to reduce cycle time and take advantage of high-throughput synthetic biology, while maximizing information capture.  Drawing on expertise from a broad range of quantitative sciences, including physics, computational biology, engineering, computer science, mathematics, and statistics, capabilities of the DSCB unit include predictive modeling, machine learning, statistical design and analysis, modeling and simulation, structural biology, systems biology, and high performance scientific computing.  These  proficiencies are applied to support a wide variety of efforts across Intrexon for applications such as Next Generation Sequencing analysis, enzyme evolution, protein design, strain design based on metabolic flux analysis, and fermentation condition optimization.
Data generation and analysis and the DSCB unit partner within the Company to take advantage of significant advancements in data-driven, quantitative reasoning and accelerate progress from discovery to commercialization.