为了得到那些没怎么花钱做实验，依靠挖掘别人二手数据的文章，我们对关键词进行了限定。根据三大公共疾病数据库“TCGA”“Gene expression omnibus”“arrayexpress”+bioinformatics为关键词检索了Pubmed中收录的文章，得到以下的结果，逐年SCI文章发表趋势如下。
挖掘二手数据依然可以发文章，发好文章
可以看到，今年的月平均发表量在60篇左右，考虑到年底，估计今年能达到700篇生信类SCI，单看10月以来的文章统计吧，就有101篇，分布于1~13分不等。
10~11月杂志名称
数量
IF因子
J Clin Invest
1
13.251
Nat Commun
2
11
Nucleic Acids Res
2
11
Clin Cancer Res
2
10.199
Proc Natl Acad Sci U S A
1
9
Cell Syst
1
8.982
Cell Rep
3
8.032
Int J Cancer
6
7.36
Oncogene
2
6.854
EBioMedicine
3
6.183
Cell Physiol Biochem
1
5.5
Bioinformatics
4
5.481
Hum Reprod
1
4.99
Epigenomics
1
4.979
Oral Oncol
1
4.636
Mol Cancer Res
1
4.597
Cancer Sci
1
4.372
J Cell Mol Med
1
4.302
J Leukoc Biol
1
4.224
Front Genet
1
4.151
Helicobacter
1
4.123
Prostate Cancer Prostatic Dis
1
4.099
Sci Rep
1
4
Cancer Cell Int
1
3.96
J Cell Physiol
3
3.923
Int J Biol Macromol
1
3.909
Ann Surg Oncol
1
3.857
Cancer Manag Res
3
3.702
Int J Mol Sci
1
3.687
Cell Signal
1
3.487
Biomed Pharmacother
1
3.457
Genes Chromosomes Cancer
1
3.362
Int J Oncol
2
3.333
J Cancer
1
3.249
Cancer Med
2
3.202
Immunopharmacol Immunotoxicol
1
3.118
Molecules
1
3.098
Transl Oncol
1
3.071
10~11月杂志名称
数量
IF因子
Oncol Rep
1
2.976
J Cell Biochem
3
2.959
Clin Chim Acta
1
2.926
Biosci Rep
2
2.899
J Biomed Inform
1
2.882
Int J Mol Med
2
2.784
PLoS One
2
2.766
Int J Surg
1
2.693
Onco Targets Ther
1
2.656
DNA Cell Biol
1
2.634
Biomed Res Int
1
2.583
Gene
3
2.498
J Bone Miner Metab
1
2.472
Biochem Biophys Res Commun
1
2.4
Diagn Pathol
1
2.396
Cell J
2
2.363
Biol Res
1
2.357
J Pharm Pharmacol
1
2.309
PeerJ
1
2.118
BMC Complement Altern Med
1
2.109
Arch Oral Biol
1
2.05
Pathol Oncol Res
1
1.935
Mol Med Rep
2
1.922
Oncol Lett
1
1.664
Andrologia
1
1.588
Pathol Res Pract
1
1.466
Neurol Res
1
1.449
Ren Fail
1
1.44
Clin Lab
1
0.848
首先，我们把5分以上的29篇章进行了归纳总结，发现他们分为以下几类：
10~11月高分生信类SCI赏析
杂志名称
IF因子
Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma.生信+实验（图真好看）
J Clin Invest
13.251
数据库EVmiRNA: a database of miRNA profiling in extracellular vesicles.
Nucleic Acids Res
11
Detection of epigenetic field defects using a weighted epigenetic distance-based method.算法类的
Nucleic Acids Res
11
Mutational interactions define novel cancer subgroups.多肿瘤
Nat Commun
11
A comprehensive overview of genomic imprinting in breast and its deregulation in cancer.多肿瘤
Nat Commun
11
Frequent homologous recombination deficiency in high-grade endometrial carcinomas.
Clin Cancer Res
10.199
Characterization of Alternative Splicing Events in HPV-Negative Head and Neck Squamous Cell Carcinoma Identifies an Oncogenic DOCK5 Variant.可变剪接
Clin Cancer Res
10.199
Identification and validation of a tumor-infiltrating Treg transcriptional signature conserved across species and tumor types.多肿瘤
Proc Natl Acad Sci U S A
9
A Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-β Superfamily.多肿瘤
Cell Syst
8.982
Genomic and Transcriptomic Characterization Links Cell Lines with Aggressive Head and Neck Cancers.多组学
Cell Rep
8.032
Comprehensive Molecular Characterization of the Hippo Signaling Pathway in Cancer.多肿瘤
Cell Rep
8.032
Pan-Cancer Landscape of Aberrant DNA Methylation across Human Tumors.多肿瘤
Cell Rep
8.032
Insights from multidimensional analyses of the pan-cancer DNA methylome heterogeneity and the uncanonical CpG-gene associations.多肿瘤
Int J Cancer
7.36
Age-specific genome-wide association study in glioblastoma identifies increased proportion of 'lower grade glioma'-like features associated with younger age.
Int J Cancer
7.36
A B7-CD28 family based signature demonstrates significantly different prognoses and tumor immune landscapes in lung adenocarcinoma.
Int J Cancer
7.36
Discovery and development of differentially methylated regions in human papillomavirus-related oropharyngeal squamous cell carcinoma.甲基化
Int J Cancer
7.36
Quantitative analysis of somatically-acquired and constitutive uniparental disomy in gastrointestinal cancers.多肿瘤
Int J Cancer
7.36
Identification of a five-lncRNA signature for predicting the risk of tumor recurrence in patients with breast cancer.风险预警、标志物类
Int J Cancer
7.36
Identification of microR-106b as a prognostic biomarker of p53-like bladder cancers by ActMiR.新的算法
Oncogene
6.854
Bioinformatics-based analysis reveals elevated MFSD12 as a key promoter of cell proliferation and a potential therapeutic target in melanoma.
Oncogene
6.854
The Landscape and Implications of Chimeric RNAs in Cervical Cancer.嵌合RNA研究
EBioMedicine
6.183
Histone-lysine N-methyltransferase SETD7 is a potential serum biomarker for colorectal cancer patients.
EBioMedicine
6.183
Profiles of alternative splicing in colorectal cancer and their clinical significance: A study based on large-scale sequencing data.可变剪接行为
EBioMedicine
6.183
Expression Signature and Role of miR-30d-5p in Non-Small Cell Lung Cancer: a Comprehensive Study Based on in Silico Analysis of Public Databases and in Vitro Experiments.生信+实验
Cell Physiol Biochem
5.5
TPMCalculator: one-step software to quantify mRNA abundance of genomic features.数据库类
Bioinformatics
5.481
Integrative cancer patient stratification via subspace merging.多肿瘤、算法
Bioinformatics
5.481
Edge-group sparse PCA for network-guided high dimensional data analysis.算法类
Bioinformatics
5.481
A global transcriptomic pipeline decoding core network of genes involved in stages leading to acquisition of drug-resistance to cisplatin in osteosarcoma cells.深度挖掘，结果可靠
Bioinformatics
5.481
和咱们医学相关的高分5分以上的生信SCI分为3类：
1．纯生信分析：要么有工作量、有深度，要么就是多肿瘤分析（例如聚焦于胃肠道类肿瘤）；
2．生信+实验：生信得到功能分子，靠功能和机制实验验证；
3．数据库类：处理公共数据库的数据，提供可以查询差异基因、功能解析、网络互作的功能；
首先我们还是提倡用科学实验来验证生信结果的，但是如果真的没条件做实验，，可以按照1、3的套路来。
师兄介绍一篇数据库类的文章为大家庖丁解牛：
EVmiRNA: a database of miRNA profiling in extracellular vesicles.
期刊：Nucleic Acids Research（IF=11分）
作者按这个套路先发布1.0，再发布2.0的模式，都灌了好几篇10分的文章了，羡不羡慕？
首先这篇文章的数据来源为①公共数据库中外泌体的测序、芯片数据②已发表外泌体的文献中报道的差异miRNA。
可按照组织类型来查询
结直肠癌分泌的外泌体
也可以根据miRNA的名字查询17种体液中的表达情况
其实这篇文章就是提供了可以查询、展示的方式，从科研思路的难度上来讲不难，但是对于网站建设、维护的要求更高一些。
最后，另外一种模式：以分子机制挖掘为目的，纯生信类的生信SCI，基本上都是我们以前讲过的套路了，和以下分析过程大部分都比较雷同。
多肿瘤类的文章无非就是在肿瘤类型、样本类型上、分子维度上叠加即可，以此类推，分数和工作量是成正比的。
以上高分数据库的搭建、分子机制类的纯生信分析，我们生信博士团队都可以很好滴去实现。
