SELPHI

Systematic Extraction of Linked Phospho-Interactions

Computation for Biologists

SELPHI is a computational workflow that aims to help non-bioinformaticians perform biological meaningful analyses of global phospho-proteomics datasets easily and to guide the design of downstream experiments to uncover the mechanistic details of signal transduction in their system.

What can Selphi do?


Pathway & GO Term analysis

Clustering

Visualization

Correlation Analysis

SELPHI implements a correlation and motif analysis leading to an educated guess of the flow of information in your signal transduction system all the way to the transcription factors that are affected in your conditions. This basic model of your system gives you, among other insights a suggestion of phospho-sites that are driving the information, potential kinase/phosphatase-substrate relationships and over-represented motifs.

Plus, you have access to a wealth of information for each of the predicted associated pairs integrated from a range of databases and tools, including: