Yun Ma

27 total papers · 777 total citations
17 papers, 583 citations indexed

About

Yun Ma is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Genetics. According to data from OpenAlex, Yun Ma has authored 17 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cellular and Molecular Neuroscience, 4 papers in Molecular Biology and 4 papers in Genetics. Recurrent topics in Yun Ma's work include Neuropeptides and Animal Physiology (5 papers), Cancer, Stress, Anesthesia, and Immune Response (4 papers) and Estrogen and related hormone effects (3 papers). Yun Ma is often cited by papers focused on Neuropeptides and Animal Physiology (5 papers), Cancer, Stress, Anesthesia, and Immune Response (4 papers) and Estrogen and related hormone effects (3 papers). Yun Ma collaborates with scholars based in United States, China and Denmark. Yun Ma's co-authors include Florent Elefteriou, Xiangli Yang, Jeffry S. Nyman, Andries Zijlstra, Daniel S. Perrien, Niki Penner, Julie A. Sterling, James Campbell, Steve Muñoz and Tao Huan and has published in prestigious journals such as Journal of Biological Chemistry, Development and Endocrinology.

In The Last Decade

Yun Ma

16 papers receiving 578 citations

Author Peers

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

Author						Papers	Cites
Yun Ma	184	151	123	109	86	17	583
Lucile Vincent	94 0.5×	124 0.8×	90 0.7×	25 0.2×	164 1.9×	15	667
Josep Blanch	159 0.9×	137 0.9×	81 0.7×	52 0.5×	32 0.4×	30	629
Susanne Syberg	185 1.0×	64 0.4×	43 0.3×	72 0.7×	90 1.0×	18	629
Linda V. Blomster	138 0.8×	48 0.3×	85 0.7×	27 0.2×	66 0.8×	21	690
Tatjana Bordukalo-Nikšić	189 1.0×	47 0.3×	115 0.9×	52 0.5×	59 0.7×	35	575
Chih‐Chin Heather Hsu	85 0.5×	43 0.3×	55 0.4×	64 0.6×	49 0.6×	21	524
Ester Reggio	90 0.5×	148 1.0×	78 0.6×	32 0.3×	46 0.5×	22	651
Philip J. Medeiros	89 0.5×	58 0.4×	65 0.5×	47 0.4×	127 1.5×	22	517
Sheng-Feng Hsu	202 1.1×	22 0.1×	105 0.9×	75 0.7×	99 1.2×	23	653
Angelo Attanasio	189 1.0×	106 0.7×	70 0.6×	26 0.2×	105 1.2×	17	662

Countries citing papers authored by Yun Ma

Since Specialization

Citations

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

Fields of papers citing papers by Yun Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yun Ma

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