Yang Jin

1.0k total citations
10 papers, 809 citations indexed

About

Yang Jin is a scholar working on Epidemiology, Molecular Biology and Cell Biology. According to data from OpenAlex, Yang Jin has authored 10 papers receiving a total of 809 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Epidemiology, 4 papers in Molecular Biology and 2 papers in Cell Biology. Recurrent topics in Yang Jin's work include Autophagy in Disease and Therapy (7 papers), Influenza Virus Research Studies (2 papers) and COVID-19 epidemiological studies (2 papers). Yang Jin is often cited by papers focused on Autophagy in Disease and Therapy (7 papers), Influenza Virus Research Studies (2 papers) and COVID-19 epidemiological studies (2 papers). Yang Jin collaborates with scholars based in United States, South Korea and China. Yang Jin's co-authors include Augustine M.K. Choi, Stefan W. Ryter, Seon‐Jin Lee, Emeka Ifedigbo, Jiaofei Cao, Hilaire C. Lam, Harikrishnan Parameswaran, Zhi-Hua Chen, Akihiko Tanaka and Hong Pyo Kim and has published in prestigious journals such as Proceedings of the National Academy of Sciences, American Journal of Respiratory and Critical Care Medicine and Journal of Medical Internet Research.

In The Last Decade

Yang Jin

10 papers receiving 806 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yang Jin United States	8	503	403	218	115	94	10	809
Veronica Della Latta Italy	6	274 0.5×	286 0.7×	292 1.3×	44 0.4×	34 0.4×	12	785
Danyi Yang China	14	163 0.3×	260 0.6×	76 0.3×	111 1.0×	28 0.3×	28	720
Jie-Sen Zhou China	13	157 0.3×	189 0.5×	194 0.9×	44 0.4×	43 0.5×	20	491
Zijing Zhu China	18	114 0.2×	402 1.0×	52 0.2×	112 1.0×	57 0.6×	45	789
Wenhua Shi China	18	134 0.3×	407 1.0×	280 1.3×	152 1.3×	75 0.8×	35	788
Yu Peng China	19	165 0.3×	519 1.3×	102 0.5×	242 2.1×	31 0.3×	50	962
Miaoxia Pan China	10	143 0.3×	262 0.7×	107 0.5×	65 0.6×	18 0.2×	15	516
Tejasav S. Sehrawat United States	14	560 1.1×	265 0.7×	50 0.2×	95 0.8×	63 0.7×	27	948
Ghulam Ilyas United States	5	390 0.8×	238 0.6×	29 0.1×	49 0.4×	46 0.5×	16	641

Countries citing papers authored by Yang Jin

Since Specialization

Citations

This map shows the geographic impact of Yang 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 Yang Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yang Jin more than expected).

Fields of papers citing papers by Yang Jin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yang 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 Yang Jin. The network helps show where Yang Jin may publish in the future.

Co-authorship network of co-authors of Yang Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Jin. A scholar is included among the top collaborators of Yang 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 Yang Jin. Yang 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:

10 of 10 papers shown

Wang, Qing, Mengmeng Jia, Yang Jin, et al.. (2023). Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis. JMIR Public Health and Surveillance. 9. e44970–e44970. 10 indexed citations

Yang, Liuyang, Yang Jin, Ting Zhang, et al.. (2023). Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation. Journal of Medical Internet Research. 25. e44238–e44238. 16 indexed citations

Moon, Hyung‐Geun, et al.. (2014). Cross-talk between apoptosis and autophagy in lung epithelial cell death.. PubMed. 2(2). 99–109. 4 indexed citations

Liang, Xiaoliang, Shuquan Wei, Seon‐Jin Lee, et al.. (2013). p62 Sequestosome 1/Light Chain 3b Complex Confers Cytoprotection on Lung Epithelial Cells after Hyperoxia. American Journal of Respiratory Cell and Molecular Biology. 48(4). 489–496. 33 indexed citations

Jin, Yang. (2013). Formation Mechanism of No.1 Part Slide of Huangtupo Landslide in the Three Gorges Reservoir Area. Earth Science(Journal of China University of Geosciences). 6 indexed citations

Jin, Yang, Akihiko Tanaka, Augustine M.K. Choi, & Stefan W. Ryter. (2012). Autophagic proteins. Autophagy. 8(3). 426–428. 34 indexed citations

Tanaka, Akihiko, Yang Jin, Seon‐Jin Lee, et al.. (2011). Hyperoxia-Induced LC3B Interacts with the Fas Apoptotic Pathway in Epithelial Cell Death. American Journal of Respiratory Cell and Molecular Biology. 46(4). 507–514. 107 indexed citations

Lee, Seon‐Jin, et al.. (2011). Beclin 1 deficiency is associated with increased hypoxia-induced angiogenesis. Autophagy. 7(8). 829–839. 109 indexed citations

Chen, Zhi-Hua, Hilaire C. Lam, Yang Jin, et al.. (2010). Autophagy protein microtubule-associated protein 1 light chain-3B (LC3B) activates extrinsic apoptosis during cigarette smoke-induced emphysema. Proceedings of the National Academy of Sciences. 107(44). 18880–18885. 310 indexed citations

10.

Lee, Seon‐Jin, Lanping Guo, Molong Li, et al.. (2010). Autophagic Protein LC3B Confers Resistance against Hypoxia-induced Pulmonary Hypertension. American Journal of Respiratory and Critical Care Medicine. 183(5). 649–658. 180 indexed citations

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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