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

Donghyun Tae, Junhee Seok

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)3741-3743
Number of pages3
JournalBioinformatics (Oxford, England)
Volume34
Issue number21
DOIs
Publication statusPublished - 2018 Nov 1

    Fingerprint

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this