Meng Dai

98 total papers · 2.9k total citations
54 papers, 1.2k citations indexed

About

Meng Dai is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Meng Dai has authored 54 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 8 papers in Pulmonary and Respiratory Medicine and 8 papers in Cancer Research. Recurrent topics in Meng Dai's work include PI3K/AKT/mTOR signaling in cancer (5 papers), Ferroptosis and cancer prognosis (5 papers) and Antioxidant Activity and Oxidative Stress (4 papers). Meng Dai is often cited by papers focused on PI3K/AKT/mTOR signaling in cancer (5 papers), Ferroptosis and cancer prognosis (5 papers) and Antioxidant Activity and Oxidative Stress (4 papers). Meng Dai collaborates with scholars based in China, United States and Hong Kong. Meng Dai's co-authors include Guang Ning, Weiqing Wang, Min Xu, M Kellis, Yu Xu, Jie Hong, Xiao Li, Yufang Bi, Weiqiong Gu and Chin‐Lee Wu and has published in prestigious journals such as Blood, Bioinformatics and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Meng Dai

52 papers receiving 1.2k citations

Author Peers

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

Author Last Decade Papers Cites
Meng Dai 576 190 171 135 123 54 1.2k
Yaowen Fu 531 0.9× 118 0.6× 173 1.0× 111 0.8× 138 1.1× 59 1.4k
Peng Zhao 344 0.6× 144 0.8× 134 0.8× 108 0.8× 63 0.5× 47 1.1k
Yuguang Zhao 527 0.9× 159 0.8× 111 0.6× 74 0.5× 88 0.7× 54 1.3k
Yukinori Tamura 416 0.7× 145 0.8× 275 1.6× 50 0.4× 229 1.9× 50 1.2k
Li He 473 0.8× 117 0.6× 150 0.9× 64 0.5× 63 0.5× 53 1.2k
Melanie Tran 423 0.7× 183 1.0× 200 1.2× 43 0.3× 155 1.3× 47 1.2k
Yue Zhang 489 0.8× 289 1.5× 104 0.6× 117 0.9× 67 0.5× 114 1.4k
Aline S.C. Fabricio 466 0.8× 232 1.2× 57 0.3× 141 1.0× 140 1.1× 63 1.4k
Xueyan Wu 714 1.2× 429 2.3× 129 0.8× 72 0.5× 81 0.7× 60 1.4k
Michèle Garlatti 436 0.8× 160 0.8× 163 1.0× 357 2.6× 93 0.8× 30 1.1k

Countries citing papers authored by Meng Dai

Since Specialization
Citations

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

Fields of papers citing papers by Meng Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meng Dai

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

All Works

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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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2026