Complex systems modeling

We apply evolutionary and complex adaptive systems thinking to solving problems in biology and beyond.  We have worked extensively with physicists, biologists, ecologists, economists and business to design and build computational simulations and mathematical models to solve practical problems.  We also teach these skills to researchers, having run  workshops at the Santa Fe Institute’s Complex Systems Summer School and elsewhere. Our approach focuses on analyzing dynamics and causal relationships in the system to help understand a system’s leverage points where change can be most effective. 
Some specific projects include computational modeling in neuroscience, ecology, evolutionary biology and network and systems biology (see Projects).  We have experience in agent-based models (co-developer of the original agent-based modeling platform, Swarm), enabling us to capture the messiness in real-world systems.  Effective modeling and simulation functions as an intuition pump: enabling the understanding of broad trends within client’s problem domains without getting diverted by details.

Data analytics and visualization

Our core focus is in the computational biology and genomics space, with specializations in bioinformatics software pipeline development (PyPop, PLAAC),  next-generation sequencing (NGS) analysis (RNA-seq, ChiP-seq etc.) and cloud-based optimization and deployment (COSMOS), but have a wide-range of experience in analyzing data from other sources.

In addition to these two core services, we have experience consulting in software development, website design, scientific writing and in strategies for effective research and development teams.  Please contact us for further details.