spBIGDATA_Mathematical and Physical modeling of Single Particle Tracking - Big Data approach

点击翻译按钮获取中文摘要

Three Nobel Prizes awarded within a short five year period (2009 in Physiology or Medicine, 2012 and 2014 in Chemistry) were related to the biological mechanisms in living cells and the fluorescence-based techniques of observing these mechanisms under the microscope. This caused a dramatic increase of experimental and theoretical achievements in the study of living cells worldwide. Ultimately the accessibility of quantitative data prompted many physicists and applied mathematicians to study of single biological cells and the physiological processes running off therein. This involvement of physicists and mathematicians has led to a new level of understanding of biological systems. The current project intends to contribute to this increasingly quantitative approach of the fundamental processes of life and to provide a significant new framework to quantify and understand the ubiquitously observed anomalous dynamic processes in cells.The concept of anomalous diffusion and fractional dynamics has deeply penetrated the statistical and chemical physics communities, yet the subject has also become a major field in mathematics. Concurrently, the European Molecular Biology Laboratory (EMBL) organized a first Conference on Big Data in Biology & Health in Heidelberg this September. This timely and interdisciplinary meeting aimed to enable the European research community to participate in and help to drive the future development of big data research, as well as raise further awareness for this new and relevant research direction in the life sciences.In view of the above challenges of the analysis of big data from single particle tracking, but also with regard to the expected membership in EMBL of Poland from 2017, we propose the following research tasks: T1. Advancement of the mathematical theory of (transient) anomalous diffusionT2. Development of rigorous statistical inference methods tailored for single particle tracking (SPT) dataT3. Identification, validation and prediction of anomalous dynamics in living cells based on big data We believe that accomplishing these interdisciplinary tasks will result in many interesting discoveries not only in mathematics, but also in physics and biology. It will allow us to find proper models and to understand anomalous processes in living cells in the era of big data.