mEBT: multiple-matching evidence-based translator of murine genomic responses for human immunity studies

Abstract Summary In this paper, we introduce multiple-matching Evidence-based Translator (mEBT) to discover genomic responses from murine expression data for human immune studies, which are significant in the given condition of mice and likely have similar responses in the corresponding condition of...

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Bibliographic Details
Published in:Bioinformatics 2018-11, Vol.34 (21), p.3741-3743
Main Authors: Tae, Donghyun, Seok, Junhee
Format: Article
Language:English
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Summary:Abstract Summary In this paper, we introduce multiple-matching Evidence-based Translator (mEBT) to discover genomic responses from murine expression data for human immune studies, which are significant in the given condition of mice and likely have similar responses in the corresponding condition of human. mEBT is evaluated over multiple datasets and shows improved inter-species agreement. mEBT is expected to be useful for research groups who use murine models to study human immunity. Availability and implementation http://cdal.korea.ac.kr/mebt/ Supplementary information Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/bty431