Biomathematics
An Emerging Role in Biomedical Research and Clinical Practice
Fixing an historical disconnect: Historically, life science research has not engaged with computational strategies to any great extent (except, perhaps, for the basic statistics used by many biologists). Conversely, those historically engaged with research in mathematics and computational methods have rarely considered biological applications. As a consequence, the greater research community has remained largely unaware of the enormous potential that computational strategies offer regarding answering contemporary biological research questions. A transition in this historical disconnect is, however, now occurring -- making accessible, for the first time, answers to some of the compelling questions that 21st-century life science research is exploring.
Extracting information from data -- and knowledge from information: The information contained in experimental data becomes useful only when it translates into applicable knowledge -- and from this knowledge eventually emerge underlying principles. The process of converting data-to-information-to-knowledge-to-principles is a hallmark focus that the NIH is now aggressively pursuing (as espoused in its “roadmap” for 21st-century biomedical research). Success in this endeavor will require innovative developments, not only pertaining to life science research efforts, but also to critically important quantitative and computational support mechanisms.
Complex, high-dimensional data producing systems-level information: Technological advances of recent years now routinely generate large volumes of complex, high-dimensional data. For many bio-science research laboratories, translating this data into useful information is proving exceedingly difficult. In particular, recent explosive developments in genomics and proteomics technologies are leading the pioneering evolution of biological research to now, for the first time, examine organisms as complex, networked systems (in both space and time). Extracting information from data in this type of systems-context poses considerable challenges -- challenges that require advanced mathematical methods, implemented in novel computational strategies that maximize efficiency, and operate in a user-unbiased and highly-automated manner.
Biomathematics -- operating at the interface: Today, mathematics and computational methods are merging with biology to create a broad, new, functional interface in life science research -- biomathematics. And, in addition to propelling basic and applied life science research forward, innovations in biomathematics are, in turn, feeding back to stimulate further advances in both bio-research, as well as the computational sciences. Ultimately, the new algorithms and modeling techniques being developed to analyze life science research questions will produce fresh ideas -- ideas from which novel biological principles may ultimately arise.
Custom data analysis and modeling solutions: To facilitate applications of biomathematics to life science research problems and questions, COBRA (Customized Online Biomathematical Research Applications) provides consulting services specifically-tailored to custom data analysis solutions ... for the life sciences ... and beyond! COBRA specializes in computational modeling and data analysis of biological dynamics and applications in life science & medical/clinical research, as well as biothermodynamic applications. COBRA’s objective is to aggressively focus the methods of biomathematics and computational biology, in a collaboratively-interactive and interdisciplinary manner, to develop and implement state-of-the-art, custom computational solution strategies to analyze and model contemporary life science research data.