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Dr J P de Magalhaes
Prof N Hall
Applications accepted all year round
About the Project
Ageing is the chief biomedical challenge of the 21st century, yet it remains a major puzzle of biology. Although it is clear that the process of ageing has a strong genetic component, much work remains to elucidate how the genome regulates ageing. Our group is developing and applying computational and experimental methods to help decipher the human genome and provide new insights into the genetics of longevity, ageing and other complex traits.
We are looking for an enthusiastic and ambitious student to develop and apply sophisticated data-mining methods and computational models at the interface of biology, mathematics and computer science. The sequencing of genomes has opened unparalleled opportunities to compare multiple genomes and identify coding or DNA regulatory sequences that modulate ageing in humans or determine species differences in ageing and longevity. There is also an urgent need to understand how genes associated with ageing collectively regulate the ageing process. We are analysing gene expression data and developing gene networks to deepen our knowledge of how genes interact with each other and with the environment to gain new insights into the genetics of ageing 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.
Further details about our work on the biology and genetics of aging are available at:
http://pcwww.liv.ac.uk/~aging/
Potential applicants are encouraged to contact Dr de Magalhaes in the first instance for an informal discussion.
Training associated with this project:
This project will provide a rich and diverse training in contemporary bioinformatics techniques, genomics and biogerontology. The student will also obtain training in modern methods in genomics, including in the generation and analysis of high-throughput transcriptional data from next-generation sequencing platforms.
In addition to the generic skills training that is provided through the Institute and University PhD programme, the student will be supported by an excellent infrastructure and will work closely with experts on the biology and genetics of ageing, bioinformatics and genomics. This diverse and stimulating environment will allow a creative and talented student to develop key skills and the project is flexible enough to allow the student to develop his or her own research interests. The student will be well-prepared for a successful career in research and in biotechnology.
We are looking for an enthusiastic and ambitious student to develop and apply sophisticated data-mining methods and computational models at the interface of biology, mathematics and computer science. The sequencing of genomes has opened unparalleled opportunities to compare multiple genomes and identify coding or DNA regulatory sequences that modulate ageing in humans or determine species differences in ageing and longevity. There is also an urgent need to understand how genes associated with ageing collectively regulate the ageing process. We are analysing gene expression data and developing gene networks to deepen our knowledge of how genes interact with each other and with the environment to gain new insights into the genetics of ageing 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.
Further details about our work on the biology and genetics of aging are available at:
http://pcwww.liv.ac.uk/~aging/
Potential applicants are encouraged to contact Dr de Magalhaes in the first instance for an informal discussion.
Training associated with this project:
This project will provide a rich and diverse training in contemporary bioinformatics techniques, genomics and biogerontology. The student will also obtain training in modern methods in genomics, including in the generation and analysis of high-throughput transcriptional data from next-generation sequencing platforms.
In addition to the generic skills training that is provided through the Institute and University PhD programme, the student will be supported by an excellent infrastructure and will work closely with experts on the biology and genetics of ageing, bioinformatics and genomics. This diverse and stimulating environment will allow a creative and talented student to develop key skills and the project is flexible enough to allow the student to develop his or her own research interests. The student will be well-prepared for a successful career in research and in biotechnology.
References
Tacutu R et al. (in press) “Human Ageing Genomic Resources: Integrated databases and tools for the biology and genetics of ageing.” Nucleic Acids Research.
Wood SH et al. (in press) “Whole transcriptome sequencing of the aging rat brain reveals dynamic RNA changes in the dark matter of the genome.” AGE.
Li Y & de Magalhães JP (in press) “Accelerated protein evolution analysis reveals genes and pathways associated with the evolution of mammalian longevity.” AGE.
Wuttke D et al. (2012) “Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.” PLoS Genetics 8:e1002834.
van Dam S et al. (2012) “GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases.” BMC Genomics 13:535.
Tacutu R et al. (2012) “Prediction of C. elegans longevity genes by human and worm longevity networks.” PLoS ONE 7:e48282.
Plank M et al. (2012) “A meta-analysis of caloric restriction gene expression profiles to infer common signatures and regulatory mechanisms.” Molecular BioSystems 8:1339-1349.
Silva AS et al. (2011) “Gathering insights on disease etiology from gene expression profiles of healthy tissues.” Bioinformatics 27:3300-3305.
Freitas A et al. (2011) “A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related.” BMC Genomics 12:27.
For full list of publications see:
http://pcwww.liv.ac.uk/~aging/publications.html
Wood SH et al. (in press) “Whole transcriptome sequencing of the aging rat brain reveals dynamic RNA changes in the dark matter of the genome.” AGE.
Li Y & de Magalhães JP (in press) “Accelerated protein evolution analysis reveals genes and pathways associated with the evolution of mammalian longevity.” AGE.
Wuttke D et al. (2012) “Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.” PLoS Genetics 8:e1002834.
van Dam S et al. (2012) “GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases.” BMC Genomics 13:535.
Tacutu R et al. (2012) “Prediction of C. elegans longevity genes by human and worm longevity networks.” PLoS ONE 7:e48282.
Plank M et al. (2012) “A meta-analysis of caloric restriction gene expression profiles to infer common signatures and regulatory mechanisms.” Molecular BioSystems 8:1339-1349.
Silva AS et al. (2011) “Gathering insights on disease etiology from gene expression profiles of healthy tissues.” Bioinformatics 27:3300-3305.
Freitas A et al. (2011) “A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related.” BMC Genomics 12:27.
For full list of publications see:
http://pcwww.liv.ac.uk/~aging/publications.html
Project supervisors
Dr J P de Magalhaes's profile is coming soon
View other supervisors at University of LiverpoolProf N Hall's profile is coming soon
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