News

The Lamond Group report an Interactive Online Web App and Database for polyomics Big Data in a new manuscript in Nucleic Acids Research

Published on 11 September 2017

A new manuscript from the Lamond group, published in Nucleic Acids Research (Brenes et al., 2017), reviews the creation and functionality of the Encyclopedia of Proteome Dynamics (EPD).

On this page

Brenes et al., Review the Encyclopedia of Proteome Dynamics

A new manuscript from the Lamond group, published in Nucleic Acids Research (Brenes et al., 2017), reviews the creation and functionality of the Encyclopedia of Proteome Dynamics (EPD). The EPD is a searchable, open access online database, designed to provide a convenient, interactive interface for exploration of proteomics and polyomics data. The EPD was first introduced in 2013. Based on user feedback and to meet the challenges of growing data volumes and complexity, a major redesign of the EPD was undertaken to provide improved scalability and additional interactive features. This new version of the EPD, which was first released in March 2015, makes use of scalable noSQL (not only Structured Query Language) solutions combined with a client side JS (Java Script) library, used to visualise and analyse data interactively. The EPD includes data from many different types of proteomics experiments, performed using human cells and model organisms. The EPD currently has >100 different interactive visualizations, ranging from volcano plots to parallel coordinate plots. The type of visualization is selected to be the most appropriate for the class of information provided by each respective dataset. During the past year, the EPD has had a median of >18,450 hits and 698 unique users per day. The EPD is part of the PepTracker software suite, which includes also tools designed for convenient laboratory data management, metadata tracking and data analysis. The new manuscript in NAR describes the functionality provided by the EPD, with examples of each type of plot and their respective interactive features.

Story category Research