Haijiang Jin

448 total citations · 1 hit paper
9 papers, 279 citations indexed

About

Haijiang Jin is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Statistical and Nonlinear Physics. According to data from OpenAlex, Haijiang Jin has authored 9 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Statistical and Nonlinear Physics. Recurrent topics in Haijiang Jin's work include Complex Network Analysis Techniques (3 papers), Advanced Graph Neural Networks (3 papers) and Aortic aneurysm repair treatments (3 papers). Haijiang Jin is often cited by papers focused on Complex Network Analysis Techniques (3 papers), Advanced Graph Neural Networks (3 papers) and Aortic aneurysm repair treatments (3 papers). Haijiang Jin collaborates with scholars based in China. Haijiang Jin's co-authors include Honglin Dong, Genmao Cao, Jie Hu, Xuezhen Xuan, Ruijing Zhang, Yaling Li, Quanwang Wu, Hong Xie, Dan Liu and Yan Zhao and has published in prestigious journals such as IEEE Access, Frontiers in Microbiology and Journal of Cellular and Molecular Medicine.

In The Last Decade

Haijiang Jin

8 papers receiving 278 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

How vascular smooth muscle cell phenotype switching contributes to vascular disease

2022 209 citations Genmao Cao, Xuezhen Xuan et al. Cell Communication and Signaling profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Haijiang Jin China	4	110	57	47	45	39	9	279
Mariia Kumskova United States	9	70 0.6×	52 0.9×	34 0.7×	29 0.6×	15 0.4×	19	286
Tommi Vähäsilta Finland	10	126 1.1×	30 0.5×	23 0.5×	28 0.6×	72 1.8×	18	334
Wenjing Guo China	10	126 1.1×	41 0.7×	32 0.7×	51 1.1×	48 1.2×	21	300
Jasper A. F. Demandt Netherlands	4	101 0.9×	58 1.0×	46 1.0×	65 1.4×	45 1.2×	5	241
Koji Maruyama Japan	11	93 0.8×	65 1.1×	55 1.2×	71 1.6×	69 1.8×	24	347
Ping Gao China	11	115 1.0×	34 0.6×	44 0.9×	44 1.0×	70 1.8×	22	293
Raquel Echavarría Mexico	13	154 1.4×	73 1.3×	34 0.7×	86 1.9×	30 0.8×	25	330
Xing Lin China	11	143 1.3×	66 1.2×	60 1.3×	66 1.5×	35 0.9×	24	300
Chenfeng Mao China	9	161 1.5×	53 0.9×	48 1.0×	78 1.7×	39 1.0×	11	340
Anita Kovács‐Kása United States	9	141 1.3×	38 0.7×	91 1.9×	49 1.1×	18 0.5×	16	279

Countries citing papers authored by Haijiang Jin

Since Specialization

Citations

This map shows the geographic impact of Haijiang Jin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Haijiang Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haijiang Jin more than expected).

Fields of papers citing papers by Haijiang Jin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Haijiang Jin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Haijiang Jin. The network helps show where Haijiang Jin may publish in the future.

Co-authorship network of co-authors of Haijiang Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Haijiang Jin. A scholar is included among the top collaborators of Haijiang Jin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Haijiang Jin. Haijiang Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Xuan, Xuezhen, Yaling Li, Genmao Cao, et al.. (2025). Inhibition of Abdominal Aortic Aneurysm Progression Through the CXCL12/CXCR4 Axis via MiR206‐3p Sponge. Journal of Cellular and Molecular Medicine. 29(1). e70328–e70328. 1 indexed citations

2.

Chang, Wenkai, et al.. (2024). Genetic evidence for a causal link between gut microbiota and arterial embolism and thrombosis: a two-sample Mendelian randomization study. Frontiers in Microbiology. 15. 1396699–1396699. 1 indexed citations

3.

Wang, Ping, Heng Wang, Ruijing Zhang, et al.. (2024). Contribution of FOS in neutrophils to venous thromboembolism via miR‐144 based on bioinformatic prediction and validation. Journal of Cellular and Molecular Medicine. 28(11). e18370–e18370. 1 indexed citations

4.

Cao, Genmao, Xuezhen Xuan, Yaling Li, et al.. (2023). Single-cell RNA sequencing reveals the vascular smooth muscle cell phenotypic landscape in aortic aneurysm. Cell Communication and Signaling. 21(1). 113–113. 45 indexed citations

5.

Xuan, Xuezhen, Yaling Li, Genmao Cao, et al.. (2023). Fluoroquinolones increase susceptibility to aortic aneurysm and aortic dissection: Molecular mechanism and clinical evidence. Vascular Medicine. 28(6). 604–613. 2 indexed citations

6.

Cao, Genmao, Xuezhen Xuan, Jie Hu, et al.. (2022). How vascular smooth muscle cell phenotype switching contributes to vascular disease. Cell Communication and Signaling. 20(1). 180–180. 209 indexed citations breakdown →

7.

Jin, Haijiang, et al.. (2021). Betweenness centrality-based community adaptive network representation for link prediction. Applied Intelligence. 52(4). 3545–3558. 15 indexed citations

8.

Liu, Dan, et al.. (2020). The Deep Fusion of Topological Structure and Attribute Information for Link Prediction. IEEE Access. 8. 34398–34406. 5 indexed citations

9.

Liu, Dan, et al.. (2020). Enhanced Network Representation Learning With Community Aware and Relational Attention. IEEE Access. 8. 57136–57147.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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