Jianzhong Su

4.2k total citations
87 papers, 2.8k citations indexed

About

Jianzhong Su is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Jianzhong Su has authored 87 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 11 papers in Cancer Research and 10 papers in Genetics. Recurrent topics in Jianzhong Su's work include Epigenetics and DNA Methylation (36 papers), Genomics and Chromatin Dynamics (16 papers) and RNA modifications and cancer (14 papers). Jianzhong Su is often cited by papers focused on Epigenetics and DNA Methylation (36 papers), Genomics and Chromatin Dynamics (16 papers) and RNA modifications and cancer (14 papers). Jianzhong Su collaborates with scholars based in China, United States and Canada. Jianzhong Su's co-authors include Wei Li, Margaret A. Goodell, Qiong Wu, Hongbo Liu, Jie Lv, Mira Jeong, Yong Lei, Yung‐Hsin Huang, Xiaotian Zhang and Meng Zhou and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Nature Genetics.

In The Last Decade

Jianzhong Su

84 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jianzhong Su China	29	2.2k	551	353	201	150	87	2.8k
Hongbo Xie United States	20	2.2k 1.0×	257 0.5×	370 1.0×	205 1.0×	136 0.9×	63	2.9k
Carsten Marr Germany	27	1.6k 0.7×	315 0.6×	351 1.0×	88 0.4×	76 0.5×	103	3.1k
Ferdinando Di Cunto Italy	33	2.8k 1.3×	1.0k 1.8×	418 1.2×	191 1.0×	96 0.6×	85	3.9k
Michael Becker Germany	25	2.2k 1.0×	212 0.4×	132 0.4×	139 0.7×	188 1.3×	49	3.4k
Chandra L. Theesfeld United States	21	2.6k 1.2×	260 0.5×	515 1.5×	80 0.4×	53 0.4×	34	3.3k
Enrico Petretto United Kingdom	36	2.9k 1.3×	545 1.0×	1.1k 3.1×	344 1.7×	82 0.5×	127	5.0k
Joshua J. Waterfall United States	19	3.2k 1.5×	627 1.1×	400 1.1×	81 0.4×	45 0.3×	33	4.2k
Stefan Kirov United States	13	1.6k 0.7×	415 0.8×	371 1.1×	87 0.4×	49 0.3×	26	2.3k
Ryan K. C. Yuen Canada	27	2.2k 1.0×	395 0.7×	1.4k 4.0×	298 1.5×	43 0.3×	49	3.7k
Chunlei Wu United States	24	2.7k 1.2×	570 1.0×	1.0k 2.9×	171 0.9×	69 0.5×	58	4.5k

Countries citing papers authored by Jianzhong Su

Since Specialization

Citations

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

Fields of papers citing papers by Jianzhong Su

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianzhong Su

This figure shows the co-authorship network connecting the top 25 collaborators of Jianzhong Su. A scholar is included among the top collaborators of Jianzhong Su 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 Jianzhong Su. Jianzhong Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bai, Lei, et al.. (2025). MultiV_Nm: a prediction method for 2′-O-methylation sites based on multi-view features. Frontiers in Genetics. 16. 1608490–1608490.

Liu, Yang, Xinyu Chen, Yunlong Ma, et al.. (2024). Endogenous mutant Huntingtin alters the corticogenesis via lowering Golgi recruiting ARF1 in cortical organoid. Molecular Psychiatry. 29(10). 3024–3039. 7 indexed citations

Chen, Chong, Gang An, Xiaoguang Yu, et al.. (2024). Screening Mutations of the Monogenic Syndromic High Myopia by Whole Exome Sequencing From MAGIC Project. Investigative Ophthalmology & Visual Science. 65(2). 9–9. 2 indexed citations

Tu, Wenzhan, Cheng Zheng, Zhenhua Feng, et al.. (2023). The investigation of interaction and chaperon-like activity of α-synuclein as a protein in pathophysiology of Parkinson's disease upon direct interaction with tectorigenin. International Journal of Biological Macromolecules. 249. 125702–125702. 5 indexed citations

Rajasekaran, Karthik, Qian Ma, Levi B. Good, et al.. (2022). Metabolic modulation of synaptic failure and thalamocortical hypersynchronization with preserved consciousness in Glut1 deficiency. Science Translational Medicine. 14(665). eabn2956–eabn2956. 16 indexed citations

Liu, Jun, et al.. (2021). MMpred: a distance-assisted multimodal conformation sampling for de novo protein structure prediction. Bioinformatics. 37(23). 4350–4356. 23 indexed citations

Ma, Yunlong, Yukuan Huang, Sen Zhao, et al.. (2021). Integrative genomics analysis reveals a 21q22.11 locus contributing risk to COVID-19. Human Molecular Genetics. 30(13). 1247–1258. 32 indexed citations

Zhang, Yan, Yaru Zhang, Jun Hu, et al.. (2020). scTPA: a web tool for single-cell transcriptome analysis of pathway activation signatures. Bioinformatics. 36(14). 4217–4219. 26 indexed citations

Hou, Ping, Siqi Bao, Dandan Fan, et al.. (2020). Machine learning-based integrative analysis of methylome and transcriptome identifies novel prognostic DNA methylation signature in uveal melanoma. Briefings in Bioinformatics. 22(4). 21 indexed citations

10.

Sun, Jie, Siqi Bao, Dandan Xu, et al.. (2019). Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy. Cell Death and Disease. 10(9). 661–661. 17 indexed citations

11.

Dasgupta, Purnendu Κ., C. Phillip Shelor, Akinde F. Kadjo, et al.. (2019). Attenuation Coefficients of Tubular Conduits for Liquid Phase Absorbance Measurement: Shot Noise Limited Optimum Path Length. Analytical Chemistry. 91(15). 9481–9489. 7 indexed citations

12.

Park, Hyun Jung, Ping Ji, Soyeon Kim, et al.. (2018). 3′ UTR shortening represses tumor-suppressor genes in trans by disrupting ceRNA crosstalk. Nature Genetics. 50(6). 783–789. 124 indexed citations

13.

Wang, Shouyi, Vicky Yamamoto, Jianzhong Su, et al.. (2018). Brain Informatics. Lecture notes in computer science. 4 indexed citations

14.

Lei, Yong, Xiaotian Zhang, Jianzhong Su, et al.. (2017). Targeted DNA methylation in vivo using an engineered dCas9-MQ1 fusion protein. Nature Communications. 8(1). 16026–16026. 157 indexed citations

15.

Zhang, Min, Shaojun Zhang, Yanhua Wen, et al.. (2015). DNA Methylation Patterns Can Estimate Nonequivalent Outcomes of Breast Cancer with the Same Receptor Subtypes. PLoS ONE. 10(11). e0142279–e0142279. 9 indexed citations

16.

Wei, Yanjun, Shumei Zhang, Shipeng Shang, et al.. (2015). SEA: a super-enhancer archive. Nucleic Acids Research. 44(D1). D172–D179. 80 indexed citations

17.

Yan, Haidan, Dongwei Zhang, Hongbo Liu, et al.. (2015). Chromatin modifications and genomic contexts linked to dynamic DNA methylation patterns across human cell types. Scientific Reports. 5(1). 8410–8410. 9 indexed citations

18.

Zhang, Chunlong, Hongyan Zhao, Jie Li, et al.. (2015). The Identification of Specific Methylation Patterns across Different Cancers. PLoS ONE. 10(3). e0120361–e0120361. 44 indexed citations

19.

Su, Jianzhong, Xiujuan Shao, Hongbo Liu, et al.. (2011). Genome-wide dynamic changes of DNA methylation of repetitive elements in human embryonic stem cells and fetal fibroblasts. Genomics. 99(1). 10–17. 39 indexed citations

20.

Han, Baohui, et al.. (2002). [The relationship between drug sensitivity and expression of drug resistance gene mutations in non-small cell lung cancer].. PubMed. 25(12). 727–31. 3 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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