Paul Skipp is Professor in Proteomics within Biological Sciences at the University of Southampton.
2016-2020: Associate Professor. University of Southampton, UK.
2013-2016: Lecturer. University of Southampton, UK.
1990-2014: Experimental Officer. University of Southampton, UK.
Paul Skipp is Professor in Proteomics and Director of the Centre for Proteomic Research at the University of Southampton. He leads research across the University in the area of Precision Medicine and molecular phenotyping with a primary focus on using proteomics and multi-dimensional data analytics to answer a range of complex biological problems across a broad range of biological research areas, including clinical proteomics, microbial proteomics, marine organisms, cell biology, and systems biology. A large focus of his research is in the area clinical proteomics, working with both academic labs and pharmaceutical companies across the areas of respiratory, allergy, infection and cancer, applying and developing Precision Medicine based approaches to generate a better understanding for the diagnosis, stratification and treatment of disease. He is also a founder and Director of the University spin-out TopMD Precision Medicine Ltd, an artificial intelligence company created to advance Precision Medicine through rapid discovery of pathway biomarkers for precise diagnosis and prognosis informing therapeutic treatment. (see also, Future Worlds).
Our research at the Centre for Proteomic Research combines in-depth expertise with internationally competitive facilities for the large-scale characterisation of proteins expressed in health and disease. This involves the application of a number of analytical proteomic and multi-dimensional data analysis technologies to solve a range of biological problems in a wide variety of organisms/tissues.
ABC Discover –funded by the charity Against Breast Cancer, we are using precision medicine approaches to understand how diet and life-style factors impact disease recurrence/progression and discover new risk and early diagnostic biomarkers of metastatic breast cancer.
Respiratory Disease – we have several projects that focus on the identification of biomarkers of airway disease for disease stratification to improve prediction of therapeutic efficacy, identify novel targets and bring understanding to their underpinning molecular mechanisms (e.g. U-BioPRED, SoMOSA, H2020 Dragon. P4O2)
Immunopeptidomics - we are using our immunopeptidomics platform for the discovery of peptide neoantigens from patient tumors for personalised cancer vaccine development in collaboration with the Centre for Cancer Immunology; in allergy studying the mechanisms of chemical sensitisation and in the area of infection, characterising peptides presented on the host cell surface by pathogens in both health and disease.
ImmunoSENSE/QSENSE/AeroSENSE/OxiSENSE – we are using novel proteomic labeling strategies to bring novel insight into the potency and the mechanism of action of small chemical sensitisers to advance the development of in-silico models to replace animal testing.
H2020 DRAGON – development of a patient-centred artificial intelligence platform enabling more rapid and precise diagnosis and prognosis of COVID-19 through molecular phenotyping and medical imaging
Computational and Systems Biology
Neuroscience, Plants and Food Security , Developmental Biology, Molecular and Cellular Biosciences, Microbiology
A large and mostly unstructured protein Spc105/KNL1 is an essential element of the eukaryotic kinetochore. The project addresses a question of how this protein performs its function as a binding platform for multiple regulatory components to control the proper chromosome segregation during mitosis.
Parkinson, E., Skipp, P.J., Aleksic, M., Scott, D.J., Clough, G and O'Connor, C.D. (2009) Quantitative Proteomic Analysis of SDS-induced Responses in Human Skin. Molecular and Cellular Proteomics (submitted)
Jones, B.M., Edwards, R.J, Skipp, P.J., O’Connor, C.D., Iglesias-Rodriguez, M.D., (2009) Shotgun proteomic analysis of Emiliania huxleyi, a marine phytoplankton species of major biogeochemical importance. Proteomics (submitted)
Mary I, Law A, Skipp P, Holland R, Topping J, Tarran G, Scanlan, DJ, O’Connor CD, Burkill PH and Zubkov MV (2009). Flow cytometric sorting of microwave fixed microbial cells for genomic and proteomic analyses. Limnology and Oceanography (submitted)
O'Connor, C.D., Clarke, I.N. and Skipp, P. (2006) Quest for complete proteome coverage. In: Microbial Proteomics: Functional Biology of Whole Organisms. Wiley, New York . Edited by I. Humphery-Smith and M. Hecker. pp. 27-38.
O'Connor, C.D., Clarke, I.N. and Skipp, P. (2006) Quest for complete proteome coverage. Methods Biochem Anal, 49, 27-38.
Skipp, P., Farooqui, M., Pickard, K., Li, Y., Evans, A.G.R. and O'Connor, C.D. (2004) . Expanding the information window to increase proteomic sensitivity and selectivity. In: Proceedings of NATO Advanced workshop on Proteomics and Toxicogenomics. Edited by J.J. Valdes and J.W. Sekowski. IOS Press, Amsterdam, The Netherlands , pp. 33-42.
Skipp, P., Farooqui, M., Evans, A. and O'Connor, C.D. (2002) Desorption/Ionisation on Silicon (DIOS): Highly reproducible, enhanced surfaces for proteomics. Molec. Cell. Proteomics 1, 690.
O'Connor, C.D., Adams, P., Alefounder, P., Farris, M., Kinsella, N., Li, Y., Payot , S., and Skipp, P. (2000) The analysis of microbial proteomes: strategies and data exploitation. Electrophoresis. 21, 1178 - 1186
Masters of Research in Big Data Biology – Joint programme lead
BIOL2011 – Molecular Biochemistry – Module coordinator
Lecturer
BIOL1007/1013 Macromolecules of Life
BIOL3063 – Bioinformatics and Systems Biology
BIOL6084 – MSc Advanced Neuroscience
BIOL3058 – Bioscience Business
BIOL3034 – In depth research project
CHEM6125 – Mass Spectrometry: Theory and Application
MEDI6227 – Quantitative Biology
MEDI6230 – Advanced Bioinformatics
Centre Director Centre for Proteomic Research
The Centre for Proteomic Research combines in-depth expertise with internationally competitive facilities for the large-scale characterisation of proteins expressed in health and disease. This involves the application of a number of analytical proteomic and multi-dimensional data analysis technologies to solve a range of biological problems in a wide variety of organisms/tissues.
Room Number : 85/5143