Home // International Journal On Advances in Software, volume 9, numbers 1 and 2, 2016 // View article

A Framework for Big Metabolomic Data Management and Analysis

Authors:
Xiangyu Li
Leiming Yu
David Kaeli
Yuanyuan Yao
Poguang Wang
Roger Giese
Vicent Yusa
Akram Alshawabkeh

Keywords: preterm birth; database; MSDA Toolbox; machine learning

Abstract:
Preterm birth is one of the major contributing factors to infant death. In the Puerto Rico Testsite for Exploring Contamination Threats Center we explore a variety of risk factors for preterm birth in Puerto Rico, including environmental, genetic and demographic factors. Given the challenge of managing such a large amount data, we have constructed a customized database specifically designed for managing our data and for facilitating efficient analysis. In this paper, we present our database design and open source Mass Spectrometry Data Analysis Toolbox. Our design allows for the efficient handling of storage and computation during metabolomic analysis. The Toolbox enables supports and end-to-end analysis protocol, from data processing and feature selection, to machine learning and visualization.

Pages: 50 to 61

Copyright: Copyright (c) to authors, 2016. Used with permission.

Publication date: June 30, 2016

Published in: journal

ISSN: 1942-2628