今天看到一個(gè)不用版面費(fèi)的期刊竟然出版了一篇非常簡(jiǎn)單的純生信數(shù)據(jù)挖掘的文章,這篇文章就做了GEO數(shù)據(jù)的差異分析、GO富集分析、KEGG富集分析、PPI分析,連生存分析都沒(méi)有做的。這個(gè)不用版面費(fèi)的期刊就是:Med Oncol,選擇非OA不需要版面費(fèi),影響因子:2.834,中科院最新分區(qū):4區(qū),不在中科院預(yù)警名單內(nèi),審稿周期比較快:約2個(gè)月。
這篇文章于2021年1月7日在Med Oncol出版,文章題目如下:
Integration of gene expression data identifies key genes and pathways in colorectal cancer
文章摘要:
Colorectal cancer (CRC) is one of the most common malignant tumor and prevalent cause of cancer-related death worldwide. In this study, we analyzed the gene expression profiles of patients with CRC with the aim of better understanding the molecular mechanism and key genes in CRC. Four gene expression profiles including, GSE9348, GSE41328, GSE41657, and GSE113513 were downloaded from GEO database. The data were processed using R programming language, in which 319 common differentially expressed genes including 94 up-regulated and 225 down-regulated were identified. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were conducted to find the most significant enriched pathways in CRC. Based on the GO and KEGG pathway analysis, the most important dysregulated pathways were regulation of cell proliferation, biocarbonate transport, Wnt, and IL-17 signaling pathways, and nitrogen metabolism. The protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software and hub genes including MYC, CXCL1, CD44, MMP1, and CXCL12 were identified as the most critical hub genes. The present study enhances our understanding of the molecular mechanisms of the CRC, which might potentially be applied in the treatment strategies of CRC as molecular targets and diagnostic biomarkers.
總結(jié):
像這種只做了GEO數(shù)據(jù)的差異分析、GO富集分析、KEGG富集分析、PPI分析的簡(jiǎn)單而又爛大街的文章,一般很多1-2分的OA期刊(需要收取昂貴版面費(fèi))都很容易秒拒,沒(méi)有想到這個(gè)不需要版面費(fèi)的Med Oncol竟然敢接收這樣的文章,所以說(shuō)只有嘗試過(guò)才知道文章的命運(yùn)會(huì)怎么樣。
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