Shumin Wu

1.2k total citations
29 papers, 753 citations indexed

About

Shumin Wu is a scholar working on Molecular Biology, Artificial Intelligence and Management Information Systems. According to data from OpenAlex, Shumin Wu has authored 29 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 9 papers in Artificial Intelligence and 2 papers in Management Information Systems. Recurrent topics in Shumin Wu's work include Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers) and Epigenetics and DNA Methylation (5 papers). Shumin Wu is often cited by papers focused on Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers) and Epigenetics and DNA Methylation (5 papers). Shumin Wu collaborates with scholars based in United States, China and United Kingdom. Shumin Wu's co-authors include Judd C. Rice, Kyoko Yokomori, Marc W. Kirschner, Xiangduo Kong, Weiping Wang, Miou Zhou, Raymond C. Trievel, Shan Huang, Yoshitake Sano and Hong Wu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Neuron.

In The Last Decade

Shumin Wu

27 papers receiving 737 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shumin Wu United States	12	495	80	79	68	67	29	753
Satoshi Okawa Japan	17	811 1.6×	102 1.3×	51 0.6×	100 1.5×	55 0.8×	67	1.2k
Álvaro Mateos Spain	10	463 0.9×	40 0.5×	78 1.0×	91 1.3×	53 0.8×	13	680
Won‐Min Song United States	17	540 1.1×	129 1.6×	62 0.8×	44 0.6×	99 1.5×	34	1.1k
Sumit Mukherjee United States	9	817 1.7×	170 2.1×	45 0.6×	51 0.8×	58 0.9×	22	1.1k
Kai Yao China	15	666 1.3×	94 1.2×	102 1.3×	135 2.0×	42 0.6×	61	967
Saskia Freytag Australia	15	494 1.0×	111 1.4×	87 1.1×	38 0.6×	39 0.6×	46	935
Guang Shi China	20	750 1.5×	76 0.9×	118 1.5×	199 2.9×	54 0.8×	50	1.2k
Daniel G. Pankratz United States	11	559 1.1×	108 1.4×	211 2.7×	90 1.3×	114 1.7×	17	1.0k
Hassan Al‐Ali United States	17	434 0.9×	49 0.6×	53 0.7×	176 2.6×	71 1.1×	48	805
Seema Aggarwal India	7	356 0.7×	58 0.7×	81 1.0×	133 2.0×	66 1.0×	19	579

Countries citing papers authored by Shumin Wu

Since Specialization

Citations

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

Fields of papers citing papers by Shumin Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shumin Wu

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

20 of 20 papers shown

Yu, Bin, Fei Su, Shiyi Ye, et al.. (2024). Ribosomal protein L32 contributes to the growth, antibiotic resistance and virulence of Glaesserella parasuis. Frontiers in Veterinary Science. 11. 1361023–1361023.

Zhao, Shuman, Huajian Xin, Shumin Wu, Yankun Sun, & Bo Hu. (2024). Attenuation of Ultraviolet Radiation by Aerosols and Clouds in Beijing Area in 2005–2020. Atmosphere. 15(3). 311–311. 5 indexed citations

Liu, Tonghua, et al.. (2024). Simultaneous measurements on cosmic curvature and opacity using latest HII regions and H(z) observations. The European Physical Journal C. 84(1). 4 indexed citations

Lin, Ping, et al.. (2023). Current trends of high-risk gene Cul3 in neurodevelopmental disorders. Frontiers in Psychiatry. 14. 1215110–1215110. 7 indexed citations

Zhang, Feng, et al.. (2023). A Novel Standardized Collaborative Online Model for Processing and Analyzing Remotely Sensed Images in Geographic Problems. Electronics. 12(21). 4394–4394. 1 indexed citations

Zang, Xufeng, et al.. (2021). Pentacyclic triterpene carboxylic acids derivatives integrated piperazine-amino acid complexes for α-glucosidase inhibition in vitro. Bioorganic Chemistry. 115. 105212–105212. 9 indexed citations

Cheng, Jie, Yan Huang, Xiaohui Zhang, et al.. (2020). TRIM21 and PHLDA3 negatively regulate the crosstalk between the PI3K/AKT pathway and PPP metabolism. Nature Communications. 11(1). 1880–1880. 98 indexed citations

Wu, Shumin, et al.. (2020). The Influence of Learning Style and Role-play on the Group Knowledge Construction in CSCL. 217–222.

Wu, Shumin, et al.. (2019). Using Augmented Reality Technology to Learn Cube Expansion Diagram in Spatial Geometry of Elementary Mathematics. 1–6. 5 indexed citations

10.

Schubbert, Suzanne, Jing Jiao, Marcus Ruscetti, et al.. (2015). Methods for PTEN in Stem Cells and Cancer Stem Cells. Methods in molecular biology. 1388. 233–285. 13 indexed citations

11.

Gao, Liuzhou, et al.. (2015). [Synthesis and anti-proliferative activity of fluoroquinolone (rhodanine unsaturated ketone) amide derivatives].. PubMed. 50(8). 1008–12. 1 indexed citations

12.

Tuzon, Creighton T., Tanya M. Spektor, Xiaodong Kong, et al.. (2014). Concerted Activities of Distinct H4K20 Methyltransferases at DNA Double-Strand Breaks Regulate 53BP1 Nucleation and NHEJ-Directed Repair. Cell Reports. 8(2). 430–438. 69 indexed citations

13.

Hsia, Hung‐En, Rohit Kumar, Rossella Lucà, et al.. (2014). Ubiquitin E3 ligase Nedd4-1 acts as a downstream target of PI3K/PTEN-mTORC1 signaling to promote neurite growth. Proceedings of the National Academy of Sciences. 111(36). 13205–13210. 70 indexed citations

14.

Zhou, Miou, Weidong Li, Shan Huang, et al.. (2013). mTOR Inhibition Ameliorates Cognitive and Affective Deficits Caused by Disc1 Knockdown in Adult-Born Dentate Granule Neurons. Neuron. 77(4). 647–654. 85 indexed citations

15.

Tran, Linh M., Chun-Ju Chang, Seema B. Plaisier, et al.. (2012). Determining PTEN Functional Status by Network Component Deduced Transcription Factor Activities. PLoS ONE. 7(2). e31053–e31053. 8 indexed citations

16.

Wu, Shumin & Judd C. Rice. (2011). A new regulator of the cell cycle. Cell Cycle. 10(1). 68–72. 42 indexed citations

17.

Wu, Shumin, Jinho D. Choi, & Martha Palmer. (2010). Detecting Cross-lingual Semantic Similarity Using Parallel PropBanks.. Conference of the Association for Machine Translation in the Americas. 349. g4456–g4456. 4 indexed citations

18.

Wu, Shumin, Weiping Wang, Xiangduo Kong, et al.. (2010). Dynamic regulation of the PR-Set7 histone methyltransferase is required for normal cell cycle progression. Genes & Development. 24(22). 2531–2542. 110 indexed citations

19.

Wu, Shumin, Raymond C. Trievel, & Judd C. Rice. (2007). Human SFMBT is a transcriptional repressor protein that selectively binds the N‐terminal tail of histone H3. FEBS Letters. 581(17). 3289–3296. 41 indexed citations

20.

Wu, Shumin, Hamada Ghenniwa, Yue Zhang, & Weiming Shen. (2006). Personal assistant agents for collaborative design environments. Computers in Industry. 57(8-9). 732–739. 27 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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