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Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network

Overview of attention for article published in BMC Systems Biology, April 2018
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Title
Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
Published in
BMC Systems Biology, April 2018
DOI 10.1186/s12918-018-0563-0
Pubmed ID
Authors

Abbas Khan, Arif Ali, Muhammad Junaid, Chang Liu, Aman Chandra Kaushik, William C. S. Cho, Dong-Qing Wei

Abstract

Diamond-Blackfan anemia (DBA) is a congenital erythroid aplasia that usually presents in infancy. In order to explore the molecular mechanisms of wild and mutated samples from DBA patients were exposed to bioinformatics investigation. Biological network of differentially expressed genes was constructed. This study aimed to identify novel therapeutic signatures in DBA and uncovered their mechanisms. The gene expression dataset of GSE14335 was used, which consists of 6 normal and 4 diseased cases. The gene ontology (GO), as well as Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and then protein-protein interaction (PPI) network of the identified differentially expressed genes (DEGs) was constructed by Cytoscape software. A total of 607 DEGs were identified in DBA, including 433 upregulated genes and 174 downregulated genes. GO analysis results showed that upregulated DEGs were significantly enriched in biological processes, negative regulation of transcription from RNA polymerase II promoter, chemotaxis, inflammatory response, immune response, positive regulation of cell proliferation, negative regulation of cell proliferation, response to mechanical stimulus, positive regulation of cell migration, response to lipopolysaccharide, and defence response. KEGG pathway analysis revealed the TNF signalling pathway, Osteoclast differentiation, Chemokine signalling pathway, Cytokine -cytokine receptor interaction, Rheumatoid arthritis, Biosynthesis of amino acids, Biosynthesis of antibiotics and Glycine, serine and threonine metabolism. The top 10 hub genes, AKT1, IL6, NFKB1, STAT3, STAT1, RAC1, EGR1, IL8, RELA, RAC3, mTOR and CCR2 were identified from the PPI network and sub-networks. The present study flagged that the identified DEGs and hub genes enrich our understanding of the molecular mechanisms underlying the development of DBA, and might shine some lights on identifying molecular targets and diagnostic biomarkers for DBA.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 12%
Student > Bachelor 3 9%
Student > Ph. D. Student 3 9%
Student > Doctoral Student 2 6%
Researcher 2 6%
Other 4 12%
Unknown 15 45%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 21%
Medicine and Dentistry 5 15%
Agricultural and Biological Sciences 2 6%
Computer Science 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 2 6%
Unknown 15 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 May 2018.
All research outputs
#20,485,225
of 23,047,237 outputs
Outputs from BMC Systems Biology
#1,011
of 1,144 outputs
Outputs of similar age
#287,526
of 326,479 outputs
Outputs of similar age from BMC Systems Biology
#33
of 47 outputs
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