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Biophysics is reshaping our perception of the epigenome: from DNA-level to high-throughput studies

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BIOPHYSICAL REPORTS
Volume 1, Issue 2, Pages -

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ELSEVIER
DOI: 10.1016/j.bpr.2021.100028

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Epigenetic research is shifting towards multidisciplinary strategies that incorporate biophysical analysis tools, in order to advance understanding of biomarkers and regulatory processes in health and disease. By integrating biophysics with bioinformatics, machine learning, and artificial intelligence, new insights into complex epigenetic processes can be gained, with potential applications in translational and clinical research. This transformation allows for the development of high-throughput applications and the utilization of advanced methods in clinical practice and diagnostics.
Epigenetic research holds great promise to advance our understanding of biomarkers and regulatory processes in health and disease. An increasing number of new approaches, ranging from molecular to biophysical analyses, enable identifying epigenetic changes on the level of a single gene or the whole epigenome. The aim of this review is to highlight how the field is shifting from completely molecular-biology-driven solutions to multidisciplinary strategies including more reliance on biophysical analysis tools. Biophysics not only offers technical advancements in imaging or structure analysis but also helps to explore regulatory interactions. New computational methods are also being developed to meet the demand of growing data volumes and their processing. Therefore, it is important to capture these new directions in epigenetics from a biophysical perspective and discuss current challenges as well as multiple applications of biophysical methods and tools. Specifically, we gradually introduce different biophysical research methods by first considering the DNA-level information and eventually higher-order chromatin structures. Moreover, we aim to highlight that the incorporation of bioinformatics, machine learning, and artificial intelligence into biophysical analysis allows gaining new insights into complex epigenetic processes. The gained understanding has already proven useful in translational and clinical research providing better patient stratification options or new therapeutic insights. Together, this offers a better readiness to transform bench-top experiments into industrial high-throughput applications with a possibility to employ developed methods in clinical practice and diagnostics.

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