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Developing and applying computational methods to study ageing and cellular rejuvenation

Principal Supervisor: Professor Joao Pedro Magalhaes

Secondary Supervisor(s): Professor Simon Jones

University of Registration: University of Birmingham

BBSRC Research Themes:

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Deadline: 4 January, 2024


Project Outline

Ageing is the chief biomedical challenge of the 21st century, yet it remains a major puzzle of biology. Recent studies have shown that cells can be rejuvenated, and biological clocks reset, using cellular reprogramming. A growing number of companies now aim to use cellular reprogramming to develop therapies for age-related diseases. These observations also raise important questions that challenge our current unidirectional view of the aging process. And if cells can be rejuvenated, could this open the door for rejuvenating organisms?

Our group is developing and applying computational and experimental methods to help decipher ageing, longevity, and rejuvenation. In this project, we are looking for an enthusiastic and ambitious student to develop and apply state-of-the-art machine learning methods and computational models at the interface of biology, mathematics, and computer science. Although cellular rejuvenation is an exciting topic, its mechanisms and pathways remain poorly understand. Moreover, the biological mechanisms behind biological clocks, like epigenetic clocks, and whether they are causes or consequences of ageing remain unknown. We are integrating multiple types of data and developing gene networks to deepen our knowledge of cellular rejuvenation and identify new candidate genes for experimental validation. The exact direction of this project, however, will be adapted to fit the research interests of the student.

Though this project is primarily computational, our lab also has wet lab facilities and thus it is possible to experimentally validate computational predictions emerging from this project.

References

  1. de Magalhães JP, Ocampo A (2022) “Cellular reprogramming and the rise of rejuvenation biotech.” Trends in Biotechnology 40:639-642.
  2. Avelar RA et al. (2020) "A multidimensional systems biology analysis of cellular senescence in ageing and disease." Genome Biology 21:91.
  3. Ocampo, A. et al. (2016) “In Vivo Amelioration of Age-Associated Hallmarks by Partial Reprogramming.” Cell 167:1719-1733

Techniques

This is a highly multidisciplinary project at the interface of life and computer sciences. As such, the project will provide a rich and diverse training in several contemporary bioinformatics techniques, AI/machine learning, cell & molecular biology, genetics and biogerontology