Systems Immunology of Malaria: an ImmPort shared data set for data mining and meta-analysis

Authors

• J Skinner
• TM Tran
• R Guja
• S Portugal
• A Ongoiba
• M Jones
• P Venepally
• J Moebius
• S Doumbo
• S Li
• E Deriso
• G Alter
• E O'Connell
• E Thomson
• PJ Dunn
• OK Doumbo
• K Kayentao
• B Traore
• EF Kirkness
• PD Crompton

Abstract

Malaria is among the world’s most deadly diseases, but the mechanisms behind acquired immunity in adults remain poorly understood, slowing the progress towards a vaccine or new therapies. As part of a larger research effort, a prospective systems biology study of 80 children subject to seasonal malaria exposure in malaria-endemic Kalifabougou, Mali. Their responses to malaria exposure during the 2011 malaria season were explored using RNA-seq, antigen protein microarray, Luminex, FACS, ELISA and other assays. These results are now shared publicly using ImmPort, a database and analysis webportal for immunological experiment data developed by Northrop Grumman Information Technology Health Solutions for the NIH/NIAID/DAIT, where all or part of the data can be re-analyzed, data mined, or included in a meta-analysis with similar malaria data sets. A random forests data mining example reveals the features identified among all experiment types that best distinguish three stages of malaria resistance among the subjects.

Scientific Focus Area: Systems Biology

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