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A new paper by Dr. M. Paola Vera-Licona and Dr. Reinhard Laubenbacher entitled “An algebra-based method for inferring gene regulatory networks” published in BMC Systems Biology has been noted as an Editor’s pick. It’s also ranked as a highly accessed article. The paper, found in BMC Systems Biology 2014, 8:37, describes a new gene regulatory network inference method based on polynomial dynamical systems incorporates time-resolved gene expression data and existing causal information and into its model inference and uses and evolutionary algorithm for parameter estimation. Congratulations Dr. Vera-Licona and Laubenbacher! Check out the paper at www.biomedcentral.com/1752-0509/8/37.
Paola Vera-Licona, Abdul Jarrah, Luis David Garcia-Puente, John McGee, Reinhard Laubenbacher. An algebra-based method for inferring gene regulatory networks. BMC Syst Biol. 2014; 8: 37. Published online 2014 March 26. doi: 10.1186/1752-0509-8-37.
We are pleased to offer a new Health Informatics Short Course on June 26, 2014 which examines informatics and data analytics for clinical and translational research. We are now accepting registrations from unior and senior researchers, faculty, postdoctoral fellows, graduate students, research assistants and associates, and clinicians who conduct clinical or translational research or who are interested in health informatics. This intensive short course examines the unique characteristics of clinical and life sciences data including the analytic principles, methods and tools for translating health data and information into actionable knowledge for improved health care. The course is presented and cosponsored by the Center for Quantitative Medicine and the CICATS Division of Biomedical Informatics. Learn more at http://cqm.uchc.edu/education/courses/data-analytics-short-course/.