Zhan Yao

5.4k total citations
39 papers, 2.9k citations indexed

About

Zhan Yao is a scholar working on Molecular Biology, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Zhan Yao has authored 39 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 12 papers in Oncology and 7 papers in Pathology and Forensic Medicine. Recurrent topics in Zhan Yao's work include Melanoma and MAPK Pathways (16 papers), PI3K/AKT/mTOR signaling in cancer (9 papers) and Cancer Mechanisms and Therapy (6 papers). Zhan Yao is often cited by papers focused on Melanoma and MAPK Pathways (16 papers), PI3K/AKT/mTOR signaling in cancer (9 papers) and Cancer Mechanisms and Therapy (6 papers). Zhan Yao collaborates with scholars based in United States, China and United Kingdom. Zhan Yao's co-authors include Neal Rosen, Elisa de Stanchina, David B. Solit, Vanessa Rodrik-Outmezguine, Neilawattie M. Torres, Anthony Tao, Yijun Gao, Rona Yaeger, Barry S. Taylor and Wenhua Li and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Zhan Yao

36 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhan Yao United States 24 2.1k 1.2k 549 521 501 39 2.9k
Sidong Huang Canada 22 1.9k 0.9× 1.2k 1.0× 518 0.9× 404 0.8× 621 1.2× 44 2.9k
Vanessa Rodrik-Outmezguine United States 16 2.1k 1.0× 943 0.8× 367 0.7× 561 1.1× 458 0.9× 32 2.8k
Steven R. Whittaker United Kingdom 20 2.3k 1.1× 1.4k 1.2× 515 0.9× 410 0.8× 419 0.8× 28 3.2k
Anthony C. Faber United States 28 2.2k 1.0× 1.4k 1.1× 323 0.6× 845 1.6× 543 1.1× 64 3.4k
Antonella Papa United States 18 2.4k 1.1× 855 0.7× 296 0.5× 390 0.7× 560 1.1× 29 3.1k
Danan Li United States 16 2.3k 1.1× 1.6k 1.3× 226 0.4× 1.0k 1.9× 496 1.0× 21 3.2k
Anurag Singh United States 19 2.8k 1.3× 2.2k 1.8× 310 0.6× 610 1.2× 1.1k 2.2× 42 4.3k
Lanxi Song United States 20 2.2k 1.0× 2.1k 1.7× 517 0.9× 701 1.3× 664 1.3× 23 3.9k
Kathryn Balmanno United Kingdom 25 2.4k 1.1× 956 0.8× 429 0.8× 198 0.4× 375 0.7× 45 3.2k
Sandra O’Toole Australia 35 2.5k 1.2× 1.9k 1.5× 356 0.6× 1.0k 2.0× 1.4k 2.7× 105 4.3k

Countries citing papers authored by Zhan Yao

Since Specialization
Citations

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

Fields of papers citing papers by Zhan Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhan Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhan Yao. A scholar is included among the top collaborators of Zhan Yao 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 Zhan Yao. Zhan Yao 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.
Li, Wenbao, et al.. (2024). The role of miRNAs as biomarkers in heterotopic ossification. EFORT Open Reviews. 9(12). 1120–1133. 1 indexed citations
2.
Alabi, Shanique, Saul Jaime‐Figueroa, Zhan Yao, et al.. (2021). Mutant-selective degradation by BRAF-targeting PROTACs. Nature Communications. 12(1). 920–920. 105 indexed citations
3.
Wang, Jiawan, Kai Pollard, Amy N. Allen, et al.. (2020). Combined Inhibition of SHP2 and MEK Is Effective in Models of NF1-Deficient Malignant Peripheral Nerve Sheath Tumors. Cancer Research. 80(23). 5367–5379. 41 indexed citations
4.
Yaeger, Rona, Daisuke Kotani, Sebastián Mondaca, et al.. (2019). Response to Anti-EGFR Therapy in Patients with BRAF non-V600–Mutant Metastatic Colorectal Cancer. Clinical Cancer Research. 25(23). 7089–7097. 85 indexed citations
5.
Gao, Yijun, Ann Maria, Na Na, et al.. (2019). V211D Mutation in MEK1 Causes Resistance to MEK Inhibitors in Colon Cancer. Cancer Discovery. 9(9). 1182–1191. 32 indexed citations
6.
Gao, Yijun, Matthew T. Chang, Daniel J. McKay, et al.. (2018). Allele-Specific Mechanisms of Activation of MEK1 Mutants Determine Their Properties. Cancer Discovery. 8(5). 648–661. 87 indexed citations
7.
Wang, Jiawan, Zhan Yao, Philip Jonsson, et al.. (2018). A Secondary Mutation in BRAF Confers Resistance to RAF Inhibition in a BRAF V600E-Mutant Brain Tumor. Cancer Discovery. 8(9). 1130–1141. 49 indexed citations
8.
Yaeger, Rona, Zhan Yao, David M. Hyman, et al.. (2017). Mechanisms of Acquired Resistance to BRAF V600E Inhibition in Colon Cancers Converge on RAF Dimerization and Are Sensitive to Its Inhibition. Cancer Research. 77(23). 6513–6523. 60 indexed citations
9.
Yao, Zhan, Rona Yaeger, Vanessa Rodrik-Outmezguine, et al.. (2017). Tumours with class 3 BRAF mutants are sensitive to the inhibition of activated RAS. Nature. 548(7666). 234–238. 349 indexed citations
10.
Trousil, Sebastian, Shuang Chen, Zhan Yao, et al.. (2017). Phenformin Enhances the Efficacy of ERK Inhibition in NF1-Mutant Melanoma. Journal of Investigative Dermatology. 137(5). 1135–1143. 19 indexed citations
11.
Xu, Jianing, Can G. Pham, Steven K. Albanese, et al.. (2016). Mechanistically distinct cancer-associated mTOR activation clusters predict sensitivity to rapamycin. Journal of Clinical Investigation. 126(9). 3526–3540. 77 indexed citations
12.
Yao, Zhan, Michael S. Dahabieh, Arjuna Rajakumar, et al.. (2015). The Role of eIF4E in Response and Acquired Resistance to Vemurafenib in Melanoma. Journal of Investigative Dermatology. 135(5). 1368–1376. 25 indexed citations
13.
Yao, Zhan, Neilawattie M. Torres, Anthony Tao, et al.. (2015). BRAF Mutants Evade ERK-Dependent Feedback by Different Mechanisms that Determine Their Sensitivity to Pharmacologic Inhibition. Cancer Cell. 28(3). 370–383. 358 indexed citations
14.
Nissan, Moriah H., Christine A. Pratilas, Alexis M. Jones, et al.. (2014). Loss of NF1 in Cutaneous Melanoma Is Associated with RAS Activation and MEK Dependence. Cancer Research. 74(8). 2340–2350. 219 indexed citations
15.
Will, Marie, Alice Can Ran Qin, Weiyi Toy, et al.. (2014). Rapid Induction of Apoptosis by PI3K Inhibitors Is Dependent upon Their Transient Inhibition of RAS–ERK Signaling. Cancer Discovery. 4(3). 334–347. 158 indexed citations
16.
Wang, Guan, Zhan Yao, Haiqing Wang, & Wenhua Li. (2011). ABT-263 sensitizes TRAIL-resistant hepatocarcinoma cells by downregulating the Bcl-2 family of anti-apoptotic protein. Cancer Chemotherapy and Pharmacology. 69(3). 799–805. 30 indexed citations
17.
Yao, Zhan, Shurong Duan, Dong Hou, et al.. (2010). B23 acts as a nucleolar stress sensor and promotes cell survival through its dynamic interaction with hnRNPU and hnRNPA1. Oncogene. 29(12). 1821–1834. 47 indexed citations
18.
Wang, Guoxing, Xiang Gao, Yun Huang, et al.. (2010). Nucleophosmin/B23 Inhibits Eg5-mediated Microtubule Depolymerization by Inactivating Its ATPase Activity. Journal of Biological Chemistry. 285(25). 19060–19067. 16 indexed citations
19.
Duan, Shurong, Zhan Yao, Yingjie Zhu, et al.. (2009). The Pirh2–keratin 8/18 interaction modulates the cellular distribution of mitochondria and UV-induced apoptosis. Cell Death and Differentiation. 16(6). 826–837. 22 indexed citations
20.

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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