Y-Y Mo

4.9k total citations · 2 hit papers
10 papers, 3.9k citations indexed

About

Y-Y Mo is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Y-Y Mo has authored 10 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 9 papers in Cancer Research and 1 paper in Oncology. Recurrent topics in Y-Y Mo's work include Cancer-related molecular mechanisms research (6 papers), RNA modifications and cancer (4 papers) and Circular RNAs in diseases (4 papers). Y-Y Mo is often cited by papers focused on Cancer-related molecular mechanisms research (6 papers), RNA modifications and cancer (4 papers) and Circular RNAs in diseases (4 papers). Y-Y Mo collaborates with scholars based in United States, China and Japan. Y-Y Mo's co-authors include Pratistha Koirala, Feng Wu, Hui Wu, Shengtao Zhu, Zhongxin Lu, Kounosuke Watabe, Meng Xu, Nanjiang Zhou, Xiang Zhang and Jianguo Huang and has published in prestigious journals such as Oncogene, Cell Death and Differentiation and Cell Death and Disease.

In The Last Decade

Y-Y Mo

10 papers receiving 3.8k 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.

miR-21-mediated tumor growth

2006 1.3k citations Shengtao Zhu, Hui Wu et al. Oncogene profile →
LncRNA-mediated regulation of cell signaling in cancer

2017 1.3k citations Pratistha Koirala, Y-Y Mo et al. Oncogene profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Y-Y Mo United States	10	3.3k	3.2k	335	210	172	10	3.9k
Youngsoo Kim United States	19	2.4k 0.7×	1.9k 0.6×	314 0.9×	208 1.0×	214 1.2×	38	2.9k
Elisa Callegari Italy	22	2.4k 0.7×	2.1k 0.6×	223 0.7×	150 0.7×	208 1.2×	39	3.1k
Fangting Wu United States	13	2.5k 0.8×	2.0k 0.6×	276 0.8×	115 0.5×	89 0.5×	19	2.9k
Beiqin Yu China	29	2.0k 0.6×	1.6k 0.5×	476 1.4×	268 1.3×	124 0.7×	65	2.7k
Zehua Bian China	27	1.9k 0.6×	1.6k 0.5×	349 1.0×	139 0.7×	208 1.2×	50	2.5k
Ji‐hang Yuan China	24	4.2k 1.3×	3.9k 1.2×	315 0.9×	247 1.2×	415 2.4×	36	4.8k
Jiaxing Zhang China	28	2.2k 0.7×	1.6k 0.5×	535 1.6×	356 1.7×	149 0.9×	60	3.0k
Tiffany Hung United States	7	4.7k 1.4×	4.4k 1.4×	186 0.6×	170 0.8×	312 1.8×	9	5.2k
Kohichi Kawahara Japan	16	1.7k 0.5×	1.2k 0.4×	246 0.7×	174 0.8×	125 0.7×	30	2.0k

Countries citing papers authored by Y-Y Mo

Since Specialization

Citations

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

Fields of papers citing papers by Y-Y Mo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Y-Y Mo. 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 Y-Y Mo. The network helps show where Y-Y Mo may publish in the future.

Co-authorship network of co-authors of Y-Y Mo

This figure shows the co-authorship network connecting the top 25 collaborators of Y-Y Mo. A scholar is included among the top collaborators of Y-Y Mo 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 Y-Y Mo. Y-Y Mo 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

1.

Koirala, Pratistha, et al.. (2017). LncRNA-mediated regulation of cell signaling in cancer. Oncogene. 36(41). 5661–5667. 1263 indexed citations breakdown →

2.

Singh, Ramesh, Shrish C. Gupta, Nanjiang Zhou, et al.. (2016). Regulation of alternative splicing of Bcl-x by BC200 contributes to breast cancer pathogenesis. Cell Death and Disease. 7(6). e2262–e2262. 126 indexed citations

3.

Chen, Bin, et al.. (2016). ERK-mediated NF-κB activation through ASIC1 in response to acidosis. Oncogenesis. 5(12). e279–e279. 71 indexed citations

4.

Gupta, Shrish C., Ramesh Singh, Jianjun Liu, et al.. (2015). Regulation of breast tumorigenesis through acid sensors. Oncogene. 35(31). 4102–4111. 67 indexed citations

5.

Xing, Fei, Sambad Sharma, Yingchao Liu, et al.. (2015). miR-509 suppresses brain metastasis of breast cancer cells by modulating RhoC and TNF-α. Oncogene. 34(37). 4890–4900. 74 indexed citations

6.

Huang, Jianguo, Nanjiang Zhou, Kounosuke Watabe, et al.. (2014). Long non-coding RNA UCA1 promotes breast tumor growth by suppression of p27 (Kip1). Cell Death and Disease. 5(1). e1008–e1008. 316 indexed citations

7.

Zhang, Zhiren, Zhe Zhu, Kounosuke Watabe, et al.. (2013). Negative regulation of lncRNA GAS5 by miR-21. Cell Death and Differentiation. 20(11). 1558–1568. 357 indexed citations

8.

Pandey, Prabhakar, Fei Xing, Sambad Sharma, et al.. (2012). Elevated lipogenesis in epithelial stem-like cell confers survival advantage in ductal carcinoma in situ of breast cancer. Oncogene. 32(42). 5111–5122. 79 indexed citations

9.

Xing, Fei, Hiroshi Okuda, Misako Watabe, et al.. (2011). Hypoxia-induced Jagged2 promotes breast cancer metastasis and self-renewal of cancer stem-like cells. Oncogene. 30(39). 4075–4086. 187 indexed citations

10.

Zhu, Shengtao, et al.. (2006). miR-21-mediated tumor growth. Oncogene. 26(19). 2799–2803. 1332 indexed citations breakdown →

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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