About this Research Topic
The last decade has seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA micro-arrays, real time medical, biological or ecological data, system control data sets, among many others. As a result, one of the most rapidly growing research fields today is the modeling of life processes in plants, animals, humans, and ecosystems using computing intensive methods that utilize principles of natural selection and artificial intelligence. Mathematical and computational approaches provide powerful tools in the study of problems in these areas. The analysis of this data poses new challenging problems and requires the development of novel mathematical and statistical models and computational methods, fueling many fascinating and fast growing research areas of modern computational biology, ecology, and statistics. The recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and have presented new challenges. In this research topic we review the most powerful and versatile computational and statistical techniques to analyze data from medical studies including but not limited to clinical trials, infectious disease incidents, ecological research, agricultural experiments, micro-array studies with the intertwining theme of implementing computing-intensive models.
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