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醫(yī)學(xué)生信分析,2020路在何方?

 yjt2004us 2020-02-14

生信數(shù)據(jù)挖掘發(fā)表SCI,為何拒稿率越來越高?因為現(xiàn)在會用R等軟件,畫個熱圖、火山圖、PPI網(wǎng)絡(luò)的人越來越多了,大家一窩蜂地每35天一篇文章的質(zhì)量去刷,可想而知數(shù)據(jù)量和作圖都是粗糙的,審稿人自然開始審美疲勞了。

不過高分的生信SCI不在少數(shù)其實,貓頭鷹博士給大家分析了一下2019年高分期刊(影響因子3.5~12分)純生信文章的統(tǒng)計結(jié)果,檢索了2019年全年,共發(fā)現(xiàn)~750篇,平均62/月。

我們按照年接收量>10篇的標(biāo)準(zhǔn)對雜志(>3.4分)統(tǒng)計,如果按照接收數(shù)量排序,J Cell Biochem3.4分)、J Cell Physiol4.5分)、Front Oncol4.13分)、Sci Rep4.011)、Front Genet3.517分)、Cancers(Basel)6.16分),如下:

純生信友好期刊

2019接收量

影響因子

J Cell Biochem

83

3.40

J Cell Physiol

68

4.50

Front Oncol

60

4.13

Sci Rep

58

4.01

Front Genet

47

3.52

Cancers (Basel)

43

6.16

Cancer Cell Int

39

3.44

Aging (Albany NY)

37

5.52

Bioinformatics

33

4.53

J Transl Med

24

4.10

Biomed Pharmacother

22

3.74

Int J Mol Sci

22

4.18

EBioMedicine

18

6.68

J Cell Mol Med

18

4.66

Nucleic Acids Res

12

11.15

Breast Cancer Res Treat

11

3.47

Epigenomics

11

4.40

Int J Cancer

11

4.98

Brief Bioinform

10

9.10

Oncogene

10

6.63

如果按照影響因子IF大小排序,如下:

純生信友好期刊

影響因子

2019接收量

Nat Commun

11.88

6

Nucleic Acids Res

11.15

12

Brief Bioinform

9.10

10

Clin Cancer Res

8.91

7

J Immunother Cancer

8.68

7

Cancer Res

8.38

5

EBioMedicine

6.68

18

Oncogene

6.63

10

Cancers (Basel)

6.16

43

Mol Oncol

5.96

7

Cell Death Dis

5.96

6

J Clin Med

5.69

7

J Exp Clin Cancer Res

5.65

7

Aging (Albany NY)

5.52

37

Clin Epigenetics

5.50

7

Oncoimmunology

5.33

6

Cancer Epidemiol Biomarkers Prev

5.06

5

Int J Cancer

4.98

11

Cancer Immunol Immunother

4.90

6

Cancer Sci

4.75

7

Cancer Gene Ther

4.68

5

J Cell Mol Med

4.66

18

Bioinformatics

4.53

33

J Cell Physiol

4.50

68

Mol Cancer Res

4.48

5

PLoS Comput Biol

4.43

5

Epigenomics

4.40

11

Gynecol Oncol

4.39

7

Int J Mol Sci

4.18

22

Front Oncol

4.13

60

J Transl Med

4.10

24

Sci Rep

4.01

58

Carcinogenesis

4.00

7

Front Pharmacol

3.85

6

Biomed Pharmacother

3.74

22

Oral Oncol

3.73

5

Ann Transl Med

3.69

6

Int J Oncol

3.57

9

Front Genet

3.52

47

Breast Cancer Res Treat

3.47

11

Life Sci

3.45

5

Cancer Cell Int

3.44

39

World J Gastroenterol

3.41

7

Mol Carcinog

3.41

5

J Cell Biochem

3.40

83


其中大于5分的雜志里Cancers (Basel)、Aging (Albany NY)、EBioMedicine對純生信類的文章最為友好的,好中一些。

我們舉例一些高分文章:

文章名

雜志

影響因子

A comprehensive PDX gastric cancer collection captures  cancer cell intrinsic transcriptional MSI traits.

Cancer Res

8.378

Identification of Coding and Long Noncoding RNAs Differentially  Expressed in Tumors and Preferentially Expressed in Healthy Tissues.(泛癌)

Identifying and targeting cancer-specific metabolism with network-based  drug target prediction.(泛癌)

EBioMedicine

6.68

Pathway-based biomarker identification with crosstalk analysis for robust prognosis prediction in  hepatocellular carcinoma.

Increased glycolysis correlates with elevated immune activity in tumor immune  microenvironment.(泛癌)

Incorporation of long non-coding RNA expression profile in the 2017 ELN risk  classification can improve prognostic prediction  of acute myeloid leukemia patients.

Identification of candidate diagnostic and prognostic biomarkers for pancreatic carcinoma.

Comprehensive characterization of the rRNA metabolism-related genes in human cancer.(泛癌)

Oncogene

6.634

Histoepigenetic analysis of HPV- and tobacco-associated head and neck cancer identifies both subtype-specific and common therapeutic targets despite  divergent microenvironments.

Identification of SERPINE1 as a Regulator of Glioblastoma Cell Dispersal  with Transcriptome Profiling

Cancers (Basel)

6.16

The YAP1-NMU Axis Is Associated with  Pancreatic Cancer Progression and Poor Outcome: Identification of a Novel  Diagnostic Biomarker and Therapeutic Target.

KRAS-Driven Lung Adenocarcinoma and B Cell Infiltration: Novel Insights for  Immunotherapy.免疫浸潤

Clinical Impact of RANK Signalling in Ovarian Cancer.

Identification of microRNAs involved in pathways which characterize the expression subtypes of NSCLC.

Mol Oncol

5.962

Identification of lncRNAs associated with early-stage  breast cancer and their prognostic implications.

Differentially expressed autophagy-related genes are potential  prognostic and diagnostic biomarkers in clear-cell renal cell carcinoma.

Aging (Albany NY)

5.515

TPM2 as a potential predictive biomarker for atherosclerosis.非腫瘤

An eight-long non-coding RNA signature as a candidate prognostic biomarker for bladder cancer.

Identification and validation of four hub genes involved in the plaque  deterioration of atherosclerosis.

Identification of potential blood biomarkers for Parkinson's disease(非腫瘤)by gene expression and DNA  methylation data integration analysis.

Clin Epigenetics

5.496


我們將高分生信SCI模式分為以下9類:
1.泛癌研究:多腫瘤組合分析,找共享基因;
2.單疾病的多組學(xué)(轉(zhuǎn)錄組、DNA甲基化、ATAC-seq)聯(lián)合分析;
3.單細胞測序數(shù)據(jù)分析:聚類分析、PCA/t-SNE降維、細胞分群、擬時分析、TCGA數(shù)據(jù)驗證的創(chuàng)新模式;
4.腫瘤類免疫浸潤分析價值分子;
5.轉(zhuǎn)錄因子-lncRNA在腫瘤發(fā)生中的分析:
6.m6A表觀遺傳組在腫瘤發(fā)病中的大數(shù)據(jù)挖掘;
等等
總之,以此類推,分?jǐn)?shù)和工作量是成正比的,貓頭鷹博士相信2020年生信分析依然大有作為。

歡迎咨詢,我們會給您提供個性化的分析方案,免費的哦。
掃碼備注:生信博士你出來

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