Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: Experimental spatial proteomics, i.e. the high-throughput assignment of proteins to sub-cellular compartments based on quantitative proteomics data, promises to shed new light on many biological processes given adequate computational tools. Results: Here  present pRoloc, a complete infrastructure to support and guide the sound analysis of quantitative massspectrometry-based spatial proteomics data. It provides functionality for unsupervised and supervised machine learning for data exploration and protein classification and novelty detection to identify new putative sub-cellular clusters. The software builds upon existing infrastructure for data management and data processing. Availability: pRoloc is implemented in the R language and available under an open-source license from the Bioconductor project (http:// www.bioconductor.org/). A vignette with a complete tutorial describing data import/export and analysis is included in the package. Test data is available in the companion package pRolocdata. Contact: lg390@cam.ac.uk
['Laurent Gatto', 'Lisa M. Breckels', 'Samuel Wieczorek', 'Thomas Burger', 'Kathryn S. Lilley']
I am writing a research paper on a idea Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata.
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