Determination of biomarkers for neonatal sepsis based on differential modules

المؤلفون المشاركون

Li, Ming
Wang, Caixia
Luan, Shaoyong
Zhang, Ruiyun
Chen, Xiuxia

المصدر

Iranian Red Crescent Medical Journal

العدد

المجلد 19، العدد 3 (31 مارس/آذار 2017)، ص ص. 1-7، 7ص.

الناشر

المستشفى الإيراني

تاريخ النشر

2017-03-31

دولة النشر

الإمارات العربية المتحدة

عدد الصفحات

7

التخصصات الرئيسية

الطب البشري

الموضوعات

الملخص EN

Background : The exact interacting factor that response to the infection for neonatal sepsis is stillneeded to urgently to be disclosed.

Objectives : This research was aimed to explore the potential biomarkers and illuminate the underlying molecular mechanisms associated with neonatal sepsis via identifying differential modules (DMs).

Methods : This is a case-control bioinformatics analysis using already published microarray data of neonatal sepsis.

This study was conducted in Qingdao, China from September 2015 to May 2016.

We recruited the gene expression profile of neonatal sepsis from the Array Express database (http://www.ebi.ac.uk/arrayexpress) under the accessing number of E-GEOD-25504, which included 27 neonatal samples with a confirmed blood culture-positive test for sepsis (bacterial infected cases) as well as 35 matched controls.

Meanwhile, the human protein-protein interaction (PPI) data was collected from the database of Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, http://string-db.org).

All of the data was preprocessed.

Then, the differential co-expression network (DCN) was constructed by integrating co-expression analysis and differential expression analysis.

Next, a systemic module searching strategy, which contained seed genes selection, module searching and refinement of modules, was performed by select DMs.

Results : Startingfromthe gene expression dataandPPI data, theDCNthat included 430 edges (covering 324 nodes)wasconstructed, in which each edge was assigned a weight value.

From the DCN, we selected a total of 16 seed genes.

Starting from these seed genes, a total of 3 modules were identified from the DCN based on the systemic module algorithm.

Of them, only one module (Module 3) was considered as DM under P < 0.05.

This DM was involved in the progress of ribosome biogenesis in eukaryotes.

Conclusions: In the present study, we identified a key gene RPS16 and a significant module involved in ribosome biogenesis in eukaryotes that were related to neonatal sepsis, which might be potential biomarkers for early detection and therapy for neonatal sepsis.

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نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Wang, Caixia& Luan, Shaoyong& Li, Ming& Zhang, Ruiyun& Chen, Xiuxia. 2017. Determination of biomarkers for neonatal sepsis based on differential modules. Iranian Red Crescent Medical Journal،Vol. 19, no. 3, pp.1-7.
https://search.emarefa.net/detail/BIM-766607

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Wang, Caixia…[et al.]. Determination of biomarkers for neonatal sepsis based on differential modules. Iranian Red Crescent Medical Journal Vol. 19, no. 3 (Mar. 2017), pp.1-7.
https://search.emarefa.net/detail/BIM-766607

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Wang, Caixia& Luan, Shaoyong& Li, Ming& Zhang, Ruiyun& Chen, Xiuxia. Determination of biomarkers for neonatal sepsis based on differential modules. Iranian Red Crescent Medical Journal. 2017. Vol. 19, no. 3, pp.1-7.
https://search.emarefa.net/detail/BIM-766607

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 6-7

رقم السجل

BIM-766607