Da Yang

19.4k citations
114 papers · 3.9k indexed · h-index 35

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Cancer Genomics and Diagnostics
    • Ovarian cancer diagnosis and treatment

Papers in

    • Cancer-related molecular mechanisms research 17
    • MicroRNA in disease regulation 11
    • Cancer Genomics and Diagnostics 8
    • Advanced Harmonic Analysis Research 19

Da Yang

112 papers receiving 3.8k citations

Peers

Da Yang
Comparison fields: 5 of 132
  • Cancer Research 1.5k
  • Reproductive Medicine 375
  • Applied Mathematics 378
  • Molecular Biology 2.4k
  • Oncology 828
Replace Joshua Gould with:
Joshua Gould United States
Hua Su China
Young‐Ho Ahn South Korea
Ed Reznik United States
Paolo Ubezio Italy
Alex Lyakhovich Russia
Robert McCormack United States
Afshin Beheshti United States
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Da Yang relative to Joshua Gould United States Joshua Gould's profile →
Citations per field
00.5×10×20×29.1×
Joshua Gould · 1×
Citations per year

Countries citing papers authored by Da Yang

Since Specialization
Citations

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

Fields of papers citing papers by Da Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Da Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Da Yang Line = papers co-authored together Da Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011413
2 2013314
3 2013173
4 2017137
5 2014116
6 2014106
7 2006106
8 2015102
9 2007101
10 201199
11 201394
12 200894
13 201987
14 201678
15 201877
16 201464
17 201962
18 201558
19 202058
20 202150

About Da Yang

Da Yang is a scholar working on Cancer Research, Applied Mathematics, Mathematical Physics, Molecular Biology and Oncology, having authored 114 papers that have together received 3.9k indexed citations. Recurring topics across this work include Advanced Harmonic Analysis Research (19 papers), Cancer-related molecular mechanisms research (17 papers), Bioinformatics and Genomic Networks (15 papers), RNA modifications and cancer (13 papers), MicroRNA in disease regulation (11 papers), RNA Research and Splicing (9 papers), Advanced Mathematical Physics Problems (8 papers) and Cancer Genomics and Diagnostics (8 papers). The work is most often cited by research in Cancer Research (1.5k citations), Reproductive Medicine (375 citations), Applied Mathematics (378 citations), Molecular Biology (2.4k citations) and Oncology (828 citations). Da Yang has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Anil K. Sood, Ilya Shmulevich, Yan Sun, Kexin Chen, Min Zhang, Sofia Khan, Kenneth R. Hess, Wei Zhang, Limei Hu and Fengxia Xue. Their work appears in journals such as Bioinformatics, Nature Communications, Science Advances, The FASEB Journal and Technology in Cancer Research & Treatment.

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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