Academic Journal

Computational Approach to Identifying Universal Macrophage Biomarkers

التفاصيل البيبلوغرافية
العنوان: Computational Approach to Identifying Universal Macrophage Biomarkers
المؤلفون: Dharanidhar Dang, Sahar Taheri, Soumita Das, Pradipta Ghosh, Lawrence S. Prince, Debashis Sahoo
المصدر: Frontiers in Physiology, Vol 11 (2020)
بيانات النشر: Frontiers Media S.A., 2020.
سنة النشر: 2020
المجموعة: LCC:Physiology
مصطلحات موضوعية: macrophage, CAD, gene expression, biomarker, Boolean analysis, Physiology, QP1-981
الوصف: Macrophages engulf and digest microbes, cellular debris, and various disease-associated cells throughout the body. Understanding the dynamics of macrophage gene expression is crucial for studying human diseases. As both bulk RNAseq and single cell RNAseq datasets become more numerous and complex, identifying a universal and reliable marker of macrophage cell becomes paramount. Traditional approaches have relied upon tissue specific expression patterns. To identify universal biomarkers of macrophage, we used a previously published computational approach called BECC (Boolean Equivalent Correlated Clusters) that was originally used to identify conserved cell cycle genes. We performed BECC analysis using the known macrophage marker CD14 as a seed gene. The main idea behind BECC is that it uses massive database of public gene expression dataset to establish robust co-expression patterns identified using a combination of correlation, linear regression and Boolean equivalences. Our analysis identified and validated FCER1G and TYROBP as novel universal biomarkers for macrophages in human and mouse tissues.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1664-042X
Relation: https://www.frontiersin.org/article/10.3389/fphys.2020.00275/full; https://doaj.org/toc/1664-042X
DOI: 10.3389/fphys.2020.00275
URL الوصول: https://doaj.org/article/3ea3ddbc8dcf42d8b3722294c5041459
رقم الانضمام: edsdoj.3ea3ddbc8dcf42d8b3722294c5041459
قاعدة البيانات: Directory of Open Access Journals
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