A TRAINING COURSE FOR PROTEOMICS DATA MANAGEMENT
Lead Research Organisation:
University of Manchester
Department Name: Life Sciences
Abstract
Proteome science is reaching maturity, and many laboratories throughout the UK have set up successful groups which are carrying out a variety of proteome experiments on different organisms, species and tissues. These experiments generate large volumes of data in a variety of different formats and styles, all containing information on the proteins that are expressed in the biological systems under study. However, it is increasingly clear that this data is not being captured, stored or managed in a consistent way, and this prevent different groups from exchanging and comparing their data sets effectively. There are, however, data standards being developed and repositories of proteome data are starting to appear. We aim to deliver a short course and associated distance learning version, which will train researchers in how to capture, analyse and store their proteomic data in a consistent fashion. By offering such professional development opportunities to scientists, we aim to promote good practice in proteome data management, help data exchange in this field, and allow more comparative proteomics and exciting experiments to be achieved.
Technical Summary
We propose to deliver a short course in Proteomics Data Management, running annually for 3 years, offering professional development training in this area. The course will be run by leading proteome bioinformaticians in the UK, offering training in a variety of aspects of the proteome data capture pipeline from the sample/hypothesis end, via database searching with mass spectrometry data, through to data storage and dissemination. This will utilise the latest data standards developed internationally for all forms of relevant proteomic data, how this is modelled computationally, captured and validated by software tools, submitted to repositories and further analysed. This will be supported by numerous exemplar cases from our own projects and collaborators, to demonstrate how proteomic data handling problems were solved, and will include extensive hands-on sessions with informatic tools to gain skills in the practice described in the course. The course will also migrate to externally delivered forms over 3 years, into Access-Grid and Distance Learning formats.
Organisations
Publications
Lau KW
(2007)
Capture and analysis of quantitative proteomic data.
in Proteomics
Lawless C
(2009)
Upstream sequence elements direct post-transcriptional regulation of gene expression under stress conditions in yeast.
in BMC genomics
Siepen JA
(2008)
ISPIDER Central: an integrated database web-server for proteomics.
in Nucleic acids research
Siepen JA
(2007)
Prediction of missed cleavage sites in tryptic peptides aids protein identification in proteomics.
in Journal of proteome research
Wright JC
(2009)
Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.
in BMC genomics
Description | We trained 3 cohorts of UK scientists in skills allied to proteomics and bioinformatics. |
Exploitation Route | As it was a training course, this does not apply in the strict "research" sense but the skills and knowledge provide lives on in the UK Science base in HEIs and Industry who are building and working on new tools in this general area. |
Sectors | Healthcare Pharmaceuticals and Medical Biotechnology |
Description | We delivered a training course in proteomics and associated bioinformatics tools, which have upskilled a large number (>30) researchers in the filed. Many are still in the field and have gone on to work in proteomics labs. Indirectly, the funds encouraged researchers to contribute to proteomics data standards |
First Year Of Impact | 2009 |
Sector | Pharmaceuticals and Medical Biotechnology |
Impact Types | Economic |