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

Thursday, September 13, 2018 — Poster Session III

12:00 p.m. – 1:30 p.m.
FAES Terrace
NIAID
SYSBIO-8

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.

Category: Systems Biology