时光如水,即便是如此艰辛坎坷的2020也已悄然离去。生活在继续,舞会从来不曾停止!在这不平凡的2020年,生信SCI发文量如何?发文趋势又如何?有哪些生信友好期刊?今天我们就来整体回顾一下2020年生信SCI文章进展!
2020年生信SCI发文量统计
小编在Pubmed中,通过“gene expression omnibus”、“TCGA”、“bioinformatics”、“biomarker”、“differentially expressed”、“protein protein interaction”、“ROC analysis”“signature”等关键词进行组合检索,再经过筛选、去重复,最终检索到2020年发表的所有生信SCI共4165篇,其中纯生信(或仅含少量表达检测)文章3194篇,剩下的971篇生信实验类文章,其包含实验占比>30%。
看到这个数据你是不是有疑惑“听说生信文章很难发了,怎么还有这么多的文章呢,而且还不缺乏高分文章”。那别人的生信文章都是怎么设计的呢?纯生信文章投哪些期刊比较容易接收呢?下面我们来一探究竟!
生信友好期刊推荐
对2020年所有生信文章的发表期刊进行统计,以下列举出接收生信文章量大于30篇的期刊,根据接收量排序如下:
2020生信友好期刊 | 接收量 | 2020-IF因子 |
Front Oncol | 181 | 4.85 |
Biomed Res Int | 154 | 2.28 |
Front Genet | 152 | 3.26 |
Aging (Albany NY) | 129 | 4.83 |
Oncol Lett | 101 | 2.31 |
PeerJ | 93 | 2.38 |
Cancer Cell Int | 87 | 4.18 |
Cancers (Basel) | 84 | 6.13 |
Sci Rep | 77 | 4.00 |
J Cancer | 71 | 3.57 |
Biosci Rep | 69 | 2.94 |
BMC Cancer | 67 | 3.15 |
Med Sci Monit | 65 | 1.92 |
Medicine (Baltimore) | 62 | 1.55 |
Cancer Manag Res | 61 | 2.89 |
Cancer Med | 58 | 3.49 |
J Cell Mol Med | 57 | 4.49 |
Ann Transl Med | 51 | 3.30 |
PLoS One | 44 | 2.74 |
J Cell Physiol | 39 | 5.55 |
J Comput Biol | 37 | 1.05 |
Mol Med Rep | 36 | 2.10 |
J Cell Biochem | 35 | 4.24 |
Int J Mol Sci | 34 | 4.56 |
J Transl Med | 34 | 4.12 |
Am J Transl Res | 33 | 3.38 |
DNA Cell Biol | 33 | 3.19 |
Technol Cancer Res Treat | 33 | 2.07 |
Front Mol Biosci | 30 | 4.19 |
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根据接收量>20篇,影响因子>3筛选条件,按照期刊影响因子排序如下:
2020生信友好期刊 | 2020-IF因子 | 接收量 |
Theranostics | 8.58 | 21 |
Cancers (Basel) | 6.13 | 84 |
Bioinformatics | 5.61 | 20 |
J Cell Physiol | 5.55 | 39 |
Front Cell Dev Biol | 5.20 | 23 |
Front Immunol | 5.09 | 22 |
Front Oncol | 4.85 | 181 |
Aging (Albany NY) | 4.83 | 129 |
Int J Mol Sci | 4.56 | 34 |
J Cell Mol Med | 4.49 | 57 |
J Cell Biochem | 4.24 | 35 |
Front Mol Biosci | 4.19 | 30 |
Cancer Cell Int | 4.18 | 87 |
J Transl Med | 4.12 | 34 |
Sci Rep | 4.00 | 77 |
J Cancer | 3.57 | 71 |
Cancer Med | 3.49 | 58 |
Cancer Biomark | 3.44 | 26 |
Oncol Rep | 3.42 | 27 |
Am J Transl Res | 3.38 | 33 |
Ann Transl Med | 3.30 | 51 |
Front Genet | 3.26 | 152 |
DNA Cell Biol | 3.19 | 33 |
BMC Cancer | 3.15 | 67 |
猫头鹰博士(微信:ipaper360) | ||
以上期刊列表绝对都能称作“生信友好期刊”了,大家有需要投稿的生信文章,可以根据影响因子在列表中选择合适的期刊哦。
生信SCI发文趋势分析
2020年年度生信SCI大赏评选正式开始!本次评选,192篇(IF>7)从4165篇生信SCI中脱颖而出。下面让我们一同欣赏这些文章亮点!
2020年生信发文趋势 | |
影响因子(IF) | 发文量 |
ALL | 4165 |
IF>3 | 2552 |
IF>5 | 613 |
IF>7 | 192 |
1.2020年最香生信SCI提名
文献标题 | 期刊 | IF |
Microbiome analyses of blood and tissues suggest cancer diagnostic approach. | Nature | 42.77 |
Genomic basis for RNA alterations in cancer. | Nature | 42.77 |
The repertoire of mutational signatures in human cancer. | Nature | 42.77 |
Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. | Nature | 42.77 |
The evolutionary history of 2,658 cancers. | Nature | 42.77 |
Patterns of somatic structural variation in human cancer genomes. | Nature | 42.77 |
Pan-cancer analysis of whole genomes. | Nature | 42.77 |
Single-Cell Analyses Identify Brain Mural Cells Expressing CD19 as Potential Off-Tumor Targets for CAR-T Immunotherapies | Cell | 38.63 |
Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing | Cell | 38.63 |
Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer | Cell | 38.63 |
Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences. | Cell | 38.63 |
能发表在Nature、Cell国际订刊上的文章能不香吗?从研究内容来看这几篇文章都是泛癌研究或者是单细胞测序研究,果然不是一般人能够驾驭的。
2.2020年最佳生信工具文章提名
文献标题 | 分类 | 期刊 | IF |
Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database. | 数据库 | Nucleic Acids Res | 11.50 |
LncTarD: a manually-curated database of experimentally-supported functional lncRNA-target regulations in human diseases. | 数据库 | Nucleic Acids Res | 11.50 |
ChimerDB 4.0: an updated and expanded database of fusion genes. | 数据库 | Nucleic Acids Res | 11.50 |
LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation. | 数据库 | Nucleic Acids Res | 11.50 |
DNMIVD: DNA methylation interactive visualization database. | 数据库 | Nucleic Acids Res | 11.50 |
SNP2APA: a database for evaluating effects of genetic variants on alternative polyadenylation in human cancers. | 数据库 | Nucleic Acids Res | 11.50 |
ncRNA-eQTL: a database to systematically evaluate the effects of SNPs on non-coding RNA expression across cancer types. | 数据库 | Nucleic Acids Res | 11.50 |
TIMER2.0 for analysis of tumor-infiltrating immune cells. | 数据库 | Nucleic Acids Res | 11.50 |
CVCDAP: an integrated platform for molecular and clinical analysis of cancer virtual cohorts. | 数据库 | Nucleic Acids Res | 11.50 |
miRactDB characterizes miRNA-gene relation switch between normal and cancer tissues across pan-cancer. | 数据库 | Brief Bioinform | 8.99 |
Network control principles for identifying personalized driver genes in cancer. | 生信 方法 | Brief Bioinform | 8.99 |
TOD-CUP: a gene expression rank-based majority vote algorithm for tissue origin diagnosis of cancers of unknown primary. | 生信 方法 | Brief Bioinform | 8.99 |
DiSNEP: a Disease-Specific gene Network Enhancement to improve Prioritizing candidate disease genes. | 生信 方法 | Brief Bioinform | 8.99 |
DeepHPV: a deep learning model to predict human papillomavirus integration sites. | 生信 方法 | Brief Bioinform | 8.99 |
Extended application of genomic selection to screen multiomics data for prognostic signatures of prostate cancer. | 生信 方法 | Brief Bioinform | 8.99 |
Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning. | 生信 方法 | Brief Bioinform | 8.99 |
CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications. | 生信 方法 | Elife | 7.08 |
sTAM: An Online Tool for the Discovery of miRNA-Set Level Disease Biomarkers. | 生信 方法 | Mol Ther Nucleic Acids | 7.03 |
Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz. | 生信 方法 | Nat Protoc | 10.41 |
A reference profile-free deconvolution method to infer cancer cell-intrinsic subtypes and tumor-type-specific stromal profiles. | 生信 方法 | Genome Med | 10.67 |
Characterization of the dual functional effects of heat shock proteins (HSPs) in cancer hallmarks to aid development of HSP inhibitors. | 生信 方法 | Genome Med | 10.67 |
CICERO: a versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data. | 生信 方法 | Genome Biol | 10.80 |
Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis. | 生信 方法 | IEEE Trans Cybern | 11.07 |
Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning. | 生信 方法 | Gut | 19.81 |
2020年发表数据库高分文章10篇,生信方法开发高分文章14篇。这些数据库及生信方法都是生信数据挖掘,文章写作的有力工具,有了这些神器加持,有木有觉得生信分析未来可期呀!(友情提示:想找不错的数据库或生信方法的文章推荐在Nucleic Acids Res、Brief Bioinform期刊查找哦!)
3.2020年单细胞生信sci提名
文献标题 | 期刊 | IF |
Single-cell transcriptome analysis reveals tumor immune microenvironment heterogenicity and granulocytes enrichment in colorectal cancer liver metastases. | Cancer Lett | 7.36 |
Network analysis of transcriptomic diversity amongst resident tissue macrophages and dendritic cells in the mouse mononuclear phagocyte system. | PLoS Biol | 7.07 |
Single-Cell Transcriptome Analysis Reveals Intratumoral Heterogeneity in ccRCC, which Results in Different Clinical Outcomes. | Mol Ther | 8.98 |
Single-Cell Transcriptome Analysis Reveals Intratumoral Heterogeneity in ccRCC, which Results in Different Clinical Outcomes. | Mol Ther | 8.98 |
Stromal cell diversity associated with immune evasion in human triple-negative breast cancer | EMBO J | 9.88 |
Malignant cell-specific CXCL14 promotes tumor lymphocyte infiltration in oral cavity squamous cell carcinoma. | J Immunother Cancer | 9.91 |
Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples. | Nucleic Acids Res | 11.50 |
A gene expression signature of TREM2 macrophages and γδ T cells predicts immunotherapy response | Nat Commun | 12.12 |
Single-cell RNA sequencing highlights the role ofinflammatory cancer-associatedfibroblasts inbladder urothelial carcinoma | Nat Commun | 12.12 |
Dissecting intratumour heterogeneity of nodal B-cell lymphomas at the transcriptional, genetic and drug-response levels | Nat Cell Biol | 20.04 |
Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue | Circulation | 23.60 |
Single-Cell Analyses Identify Brain Mural Cells Expressing CD19 as Potential Off-Tumor Targets for CAR-T Immunotherapies | Cell | 38.63 |
Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing | Cell | 38.63 |
Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer | Cell | 38.63 |
2020年发表的单细胞生信高分文章14篇,相信随着单细胞测序成本的降低及单细胞数据集的增加,单细胞生信发文势必会是下一个爆点。
4.2020年最热生信套路文章提名
(1)预后模型构建/biomarker筛选生信SCI列29篇:延续了2019年的生信研究热点,2020年诊断/预后模型、biomarker筛选的生信文章有增无减。且高分文章的生信套路得到了升级,比如糅合多个研究热点的生信套路(m6A相关的lncRNA构建肿瘤预后模型),又比如增加多个数据库的数据集及临床信息进行多角度模型验证的生信套路。总之,预后模型相关,尤其是肿瘤预后相关生信文章还是大有可为的!
(2)非编码RNA研究高分生信SCI共22篇:从这些高分文章可以看出,纯生信的ceRNA机制研究目前已经很难再发5分以上的文章了,想要发表非编码RNA研究的高分文章,生信分析加上表达量验证实验(Real-Time qPCR、Westorn Blot)体外细胞表型实验(细胞增殖/细胞凋亡/细胞迁移等实验)已成为标配。
(3)免疫治疗/免疫浸润相关生信SCI共14篇:随着肿瘤异质性、肿瘤微环境的深入研究,肿瘤治疗已进入肿瘤免疫治疗新时代。预测肿瘤复发的可能性,分析患者免疫状态,筛选诊断生物标志物等研究,利用高通量生信分析无疑是行之有效的有力手段。