Li Su

243 papers receiving 6.3k citations

Li Su's Hit Papers

A family of human cdc2‐related protein kinases. 1992 · 791 citations
7910+11+22Years since publication250500750

Peers

Li Su
Comparison fields: 5 of 157
  • Cancer Research 798
  • Oncology 1.3k
  • Pathology and Forensic Medicine 551
  • Cardiology and Cardiovascular Medicine 628
  • Molecular Biology 2.0k
Replace Chee‐Yin Chai with:
Chee‐Yin Chai Taiwan
Anthony A. Fryer United Kingdom
Christopher A. Haiman United States
Richard C. Strange United Kingdom
Stig E. Bojesen Denmark
Hiroyuki Nagase Japan
Eun Young Kim South Korea
Patricia J. Sime United States
Hong Zhao China
Lei Wang China
Li Su relative to Chee‐Yin Chai Taiwan Chee‐Yin Chai's profile →
Citations per field
00.5×1.5×2.3×
Chee‐Yin Chai · 1×
Citations per year

Countries citing papers authored by Li Su

Since Specialization
Citations

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

Fields of papers citing papers by Li Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 250 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A family of human cdc2‐related protein kinases.
Hit paper breakdown →
1992791
2 2014168
3 2015167
4 2007160
5 2014146
6 2010142
7 2012106
8 2008101
9 201093
10 200992
11 200487
12 200785
13 200985
14
Differential association of the codon 72 p53 and GSTM1 polymorphisms on histological subtype of non-small cell lung carcinoma.
200184
15 201383
16 201176
17 200870
18 200869
19 200568
20 201064

About Li Su

Li Su is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Surgery, having authored 250 papers that have together received 6.4k indexed citations. Recurring topics across this work include RNA modifications and cancer (15 papers), Esophageal Cancer Research and Treatment (13 papers), Atrial Fibrillation Management and Outcomes (12 papers), Epigenetics and DNA Methylation (10 papers), Lung Cancer Treatments and Mutations (9 papers), Cancer-related molecular mechanisms research (8 papers), Heavy Metal Exposure and Toxicity (8 papers) and Lymphoma Diagnosis and Treatment (8 papers). The work is most often cited by research in Cancer Research (798 citations), Oncology (1.3k citations), Pathology and Forensic Medicine (551 citations), Cardiology and Cardiovascular Medicine (628 citations) and Molecular Biology (2.0k citations). Li Su has collaborated with scholars based in China, United States and Canada. Frequent co-authors include David C. Christiani, Geoffrey Liu, G H Enders, Claude Gorka, Chia‐Ling Wu, Li‐Huei Tsai, Matthew Meyerson, Ed Harlow, Kofi Asomaning and Rihong Zhai. Their work appears in journals such as International Journal of Cancer, PLoS ONE, Journal of Clinical Oncology, Carcinogenesis and Cancer Epidemiology Biomarkers & Prevention.

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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