San Ming Wang

3.7k citations
99 papers · 2.6k indexed · h-index 27

Impact in

    • Cancer-related molecular mechanisms research
    • RNA Research and Splicing
    • RNA modifications and cancer
    • CRISPR and Genetic Engineering
    • Gene expression and cancer classification
    • RNA and protein synthesis mechanisms
    • Molecular Biology Techniques and Applications
    • Genomics and Phylogenetic Studies

Papers in

San Ming Wang

97 papers receiving 2.5k citations

Peers

San Ming Wang
Comparison fields: 5 of 126
  • Cancer Research 541
  • Molecular Biology 1.8k
  • Genetics 591
  • Biophysics 84
  • Oncology 262
Replace Kenneth Chang with:
Kenneth Chang United States
Judith B. Zaugg Germany
Francisco J. Iborra United Kingdom
Nina C. Hubner Germany
Fatih Ozsolak United States
Steven Wingett United Kingdom
Xiaoping Yang China
Simon J. McGowan United Kingdom
Vincent A. Blomen Netherlands
M Riggs United States
San Ming Wang relative to Kenneth Chang United States Kenneth Chang's profile →
Citations per field
00.5×1.5×2.1×
Kenneth Chang · 1×
Citations per year

Countries citing papers authored by San Ming Wang

Since Specialization
Citations

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

Fields of papers citing papers by San Ming Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by San Ming Wang. 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 San Ming Wang. The network helps show where San Ming Wang may publish in the future.

Co-authorship network

The 25 scholars most cited alongside San Ming Wang, 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 San Ming Wang Line = papers co-authored together San Ming Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20238
3 20231
4 20219
5 20217
6 201912
7 201719
8 20155
9 201516
10 201339
11 201225
12 20103
13 20103
14 2008209
15 20069
16 20057
17 200583
18 2005205
19 20036
20 20016

About San Ming Wang

San Ming Wang is a scholar working on Cancer Research, Genetics, Molecular Biology, Pathology and Forensic Medicine and Transplantation, having authored 99 papers that have together received 2.6k indexed citations. Recurring topics across this work include BRCA gene mutations in cancer (19 papers), Genomics and Phylogenetic Studies (19 papers), DNA Repair Mechanisms (17 papers), Gene expression and cancer classification (14 papers), Genomics and Chromatin Dynamics (14 papers), Cancer Genomics and Diagnostics (13 papers), Genetic factors in colorectal cancer (13 papers) and Molecular Biology Techniques and Applications (12 papers). The work is most often cited by research in Cancer Research (541 citations), Molecular Biology (1.8k citations), Genetics (591 citations), Biophysics (84 citations) and Oncology (262 citations). San Ming Wang has collaborated with scholars based in United States, Macao and China. Frequent co-authors include Jianjun Chen, Sanggyu Lee, Janet D. Rowley, Guolin Zhou, Siddharth Sinha, Xijin Ge, Yeong C. Kim, Qingfa Wu, Benjamin Tam and Terry Clark. Their work appears in journals such as Proceedings of the National Academy of Sciences, BMC Genomics, Journal of Medical Genetics, Genomics and BMC Cancer.

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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