这个不用版面费的期刊牛呀，这么简单的纯生信也敢接收

今天看到一个不用版面费的期刊竟然出版了一篇非常简单的纯生信数据挖掘的文章，这篇文章就做了GEO数据的差异分析、GO富集分析、KEGG富集分析、PPI分析，连生存分析都没有做的。这个不用版面费的期刊就是：Med Oncol，选择非OA不需要版面费，影响因子：2.834，中科院最新分区：4区，不在中科院预警名单内，审稿周期比较快：约2个月。

这篇文章于2021年1月7日在Med Oncol出版，文章题目如下：

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.

总结：

像这种只做了GEO数据的差异分析、GO富集分析、KEGG富集分析、PPI分析的简单而又烂大街的文章，一般很多1-2分的OA期刊（需要收取昂贵版面费）都很容易秒拒，没有想到这个不需要版面费的Med Oncol竟然敢接收这样的文章，所以说只有尝试过才知道文章的命运会怎么样。