Projects per year
Abstract
Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein-protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualise and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and webapplication that provides open access to integrated proteomics data for >30,000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualisations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets.
Original language | English |
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Pages (from-to) | D1202-D1209 |
Number of pages | 8 |
Journal | Nucleic Acids Research |
Volume | 46 |
Issue number | D1 |
Early online date | 7 Sept 2017 |
DOIs | |
Publication status | Published - 4 Jan 2018 |
Keywords
- big data
- proteomics
- mass spectrometry
- visualisation
- omics
- analytics
- database
- web app
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Dive into the research topics of 'The Encyclopedia of Proteome Dynamics – A big data ecosystem for (prote)omics'. Together they form a unique fingerprint.Projects
- 1 Finished
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Multidimensional Proteomic Analysis of Metabolic Stress & Cellular Phenotypes (Strategic Grant)
Cantrell, D. (Investigator) & Lamond, A. (Investigator)
1/01/15 → 31/12/19
Project: Research
Student theses
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Towards population-scale proteomics to study molecular phenotypes in health and disease
Brenes Murillo, A. (Author), Cantrell, D. (Supervisor) & Lamond, A. (Supervisor), 2023Student thesis: Doctoral Thesis › Doctor of Philosophy
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