HUPO_2011_poster.pdf (483.72 kB)
pRoloc - A unifying bioinformatics framework for organelle proteomics
poster
posted on 2017-05-25, 19:34 authored by Laurent GattoLaurent Gatto, Lisa M. Breckels, Matthew W.B. Trotter, Kathryn S. LilleyPoster presented at the HUPO conference in 2011
Reliably resolving protein localisation is not a trivial task, and requires (1) flexible, yet powerful data (and meta-data) structures, with handling and transformation capabilities, (2) efficient processing algorithms and (3) customisable data visualisation. So far, several data analysis strategies for MS-based approaches have been described in the literature, but no comparison has been attempted due to their diverse and ill-documented nature. pRoloc aims at filling this gap to provide researchers with a unified framework for MS-based protein localisation, with particular focus on gradient-based approaches.
Reliably resolving protein localisation is not a trivial task, and requires (1) flexible, yet powerful data (and meta-data) structures, with handling and transformation capabilities, (2) efficient processing algorithms and (3) customisable data visualisation. So far, several data analysis strategies for MS-based approaches have been described in the literature, but no comparison has been attempted due to their diverse and ill-documented nature. pRoloc aims at filling this gap to provide researchers with a unified framework for MS-based protein localisation, with particular focus on gradient-based approaches.