Ya Gao

34 total papers · 579 total citations
22 papers, 451 citations indexed

About

Ya Gao is a scholar working on Molecular Biology, Cell Biology and Neurology. According to data from OpenAlex, Ya Gao has authored 22 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 9 papers in Cell Biology and 4 papers in Neurology. Recurrent topics in Ya Gao's work include Zebrafish Biomedical Research Applications (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers) and Sexual Differentiation and Disorders (3 papers). Ya Gao is often cited by papers focused on Zebrafish Biomedical Research Applications (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers) and Sexual Differentiation and Disorders (3 papers). Ya Gao collaborates with scholars based in China, United States and United Kingdom. Ya Gao's co-authors include Feng Liu, Lu Wang, Yonglong Wei, Roger Patient, Qiuping He, Panpan Zhang, Dongyuan Ma, Chunxia Zhang, Sifeng Wang and Xinyan Lu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Experimental Medicine.

In The Last Decade

Ya Gao

21 papers receiving 444 citations

Author Peers

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

Author Last Decade Papers Cites
Ya Gao 290 174 105 78 53 22 451
Tomohide Suzuki 249 0.9× 224 1.3× 68 0.6× 57 0.7× 36 0.7× 13 470
Tshering Lama-Sherpa 371 1.3× 120 0.7× 87 0.8× 69 0.9× 55 1.0× 22 519
Seung‐Ryul Kim 369 1.3× 142 0.8× 89 0.8× 38 0.5× 29 0.5× 14 550
Cuiyan Xin 421 1.5× 127 0.7× 87 0.8× 31 0.4× 19 0.4× 12 532
Paul Coleman 229 0.8× 93 0.5× 87 0.8× 59 0.8× 19 0.4× 20 488
Liisa Laitinen 272 0.9× 67 0.4× 61 0.6× 56 0.7× 25 0.5× 14 492
Ying Xia 279 1.0× 93 0.5× 34 0.3× 82 1.1× 60 1.1× 20 427
Roberto Bernardoni 388 1.3× 81 0.5× 72 0.7× 37 0.5× 34 0.6× 24 535
Anita K. Stannard 194 0.7× 47 0.3× 123 1.2× 72 0.9× 38 0.7× 11 506
R K Chawla 207 0.7× 126 0.7× 60 0.6× 62 0.8× 35 0.7× 14 513

Countries citing papers authored by Ya Gao

Since Specialization
Citations

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

Fields of papers citing papers by Ya Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ya Gao

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