Lang Wu

5.2k total citations
112 papers, 2.7k citations indexed

About

Lang Wu is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Lang Wu has authored 112 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 27 papers in Genetics and 20 papers in Oncology. Recurrent topics in Lang Wu's work include Genetic Associations and Epidemiology (24 papers), Epigenetics and DNA Methylation (14 papers) and RNA modifications and cancer (11 papers). Lang Wu is often cited by papers focused on Genetic Associations and Epidemiology (24 papers), Epigenetics and DNA Methylation (14 papers) and RNA modifications and cancer (11 papers). Lang Wu collaborates with scholars based in United States, China and United Kingdom. Lang Wu's co-authors include Mingli Liu, Jingjing Zhu, Qingsen Ming, Shuqiao Yao, Qi‐Jun Wu, Ting‐Ting Gong, Changwei Li, Larry J. Prokop, M. Hassan Murad and Zhiyong Zou and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and Nature Genetics.

In The Last Decade

Lang Wu

103 papers receiving 2.6k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Lang Wu 558 408 375 316 313 112 2.7k
Sreeram V Ramagopalan 715 1.3× 559 1.4× 324 0.9× 460 1.5× 553 1.8× 161 5.5k
Min Gao 486 0.9× 442 1.1× 227 0.6× 131 0.4× 280 0.9× 102 2.3k
Anselm Mak 499 0.9× 332 0.8× 242 0.6× 209 0.7× 324 1.0× 113 5.0k
Tatjana Pekmezović 649 1.2× 298 0.7× 333 0.9× 151 0.5× 572 1.8× 327 5.4k
Monica Hultcrantz 878 1.6× 890 2.2× 320 0.9× 165 0.5× 291 0.9× 42 3.6k
Zhimei Liu 610 1.1× 551 1.4× 169 0.5× 331 1.0× 253 0.8× 135 2.6k
Kesheng Wang 783 1.4× 198 0.5× 183 0.5× 366 1.2× 190 0.6× 168 2.3k
Carol Hitchon 613 1.1× 342 0.8× 173 0.5× 598 1.9× 579 1.8× 198 5.1k
Kepher H. Makambi 445 0.8× 877 2.1× 376 1.0× 284 0.9× 160 0.5× 95 2.4k
Robin Bliss 775 1.4× 587 1.4× 246 0.7× 178 0.6× 297 0.9× 72 3.4k

Countries citing papers authored by Lang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lang Wu

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

All Works

20 of 20 papers shown
1.
Sun, Yanfa, Jingjing Zhu, Fubo Wang, et al.. (2025). Transcriptome‐Wide Association Study Identified Novel Blood Tissue Gene Biomarkers for Prostate Cancer Risk. The Prostate. 85(6). 567–579.
2.
Gong, Ting‐Ting, Fang-Hua Liu, Yifan Wei, et al.. (2024). SH3RF2 contributes to cisplatin resistance in ovarian cancer cells by promoting RBPMS degradation. Communications Biology. 7(1). 67–67. 7 indexed citations
3.
Chen, Yuhan, Jia‐Cheng Liu, Jiaxin Liu, et al.. (2024). Association between pre-diagnosis and post-diagnosis Alternate Mediterranean Diet and ovarian cancer survival: evidence from a prospective cohort study. Journal of Translational Medicine. 22(1). 860–860. 2 indexed citations
4.
Liu, Jia‐Cheng, Fanghua Liu, Deyu Zhang, et al.. (2024). Association between pre- and post-diagnosis healthy eating index 2020 and ovarian cancer survival: evidence from a prospective cohort study. Food & Function. 15(16). 8408–8417. 3 indexed citations
5.
6.
Chen, Yu, Zitong Gao, Hua Yang, et al.. (2024). Pan‐cancer analyses of bromodomain containing 9 as a novel therapeutic target reveals its diagnostic, prognostic potential and biological mechanism in human tumours. Clinical and Translational Medicine. 14(2). e1543–e1543. 11 indexed citations
7.
8.
Liu, Shuai, Hua Zhong, Jingjing Zhu, et al.. (2023). Regulome‐wide association study identifies genetically driven accessible regions associated with pancreatic cancer risk. International Journal of Cancer. 154(4). 670–678. 2 indexed citations
9.
Liu, Duo, Jingjing Zhu, Yanfa Sun, et al.. (2023). Splicing transcriptome-wide association study to identify splicing events for pancreatic cancer risk. Carcinogenesis. 44(10-11). 741–747. 2 indexed citations
10.
Tian, Yijun, Dandan Dong, Zixian Wang, et al.. (2023). Combined CRISPRi and proteomics screening reveal a cohesin-CTCF-bound allele contributing to increased expression of RUVBL1 and prostate cancer progression. The American Journal of Human Genetics. 110(8). 1289–1303. 6 indexed citations
11.
Zhong, Hua, et al.. (2023). Elucidating the role of blood metabolites on pancreatic cancer risk using two‐sample Mendelian randomization analysis. International Journal of Cancer. 154(5). 852–862. 12 indexed citations
12.
Wu, Lang, et al.. (2023). Ovarian Cancer and Parkinson’s Disease: A Bidirectional Mendelian Randomization Study. Journal of Clinical Medicine. 12(8). 2961–2961. 2 indexed citations
13.
Wu, Chong, Jonathan R. Bradley, Yanming Li, Lang Wu, & Hong‐Wen Deng. (2021). A gene-level methylome-wide association analysis identifies novel Alzheimer’s disease genes. Bioinformatics. 37(14). 1933–1940. 6 indexed citations
14.
Wu, Chong, Jingjing Zhu, Xiaoran Tong, et al.. (2021). Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi‐phased study of prostate cancer. Cancer Communications. 41(12). 1387–1397. 8 indexed citations
15.
Liu, Duo, Jingjing Zhu, Dan Zhou, et al.. (2021). A transcriptome‐wide association study identifies novel candidate susceptibility genes for prostate cancer risk. International Journal of Cancer. 150(1). 80–90. 18 indexed citations
16.
Liu, Duo, Dan Zhou, Yanfa Sun, et al.. (2020). A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Genes for Pancreatic Cancer Risk. Cancer Research. 80(20). 4346–4354. 30 indexed citations
17.
Wu, Lang, Xiang Shu, Jiandong Bao, et al.. (2019). Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk. Cancer Research. 79(18). 4592–4598. 16 indexed citations
18.
Wu, Lang, Jifeng Wang, Qiuyin Cai, et al.. (2019). Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants. Cancer Research. 79(13). 3192–3204. 37 indexed citations
19.
Wei, Jing, Ying Chen, Lei Lü, et al.. (2014). Human Umbilical Cord Blood–Derived Mesenchymal Stem Cells Producing IL15 Eradicate Established Pancreatic Tumor in Syngeneic Mice. Molecular Cancer Therapeutics. 13(8). 2127–2137. 61 indexed citations
20.
Wu, Lang, Alisa M. Goldstein, Kai Yu, et al.. (2014). Variants Associated with Susceptibility to Pancreatic Cancer and Melanoma Do Not Reciprocally Affect Risk. Cancer Epidemiology Biomarkers & Prevention. 23(6). 1121–1124. 13 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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