Michael Li

30 papers receiving 28.1k citations

Hit Papers

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms 2018 · 27.0k citations
27.0k20172026202020235.0k10.0k15.0k20.0k25.0k

Peers

Michael Li
Comparison fields: 5 of 181
  • Parasitology 1.7k
  • Endocrinology 1.3k
  • Plant Science 8.3k
  • Horticulture 215
  • Ecology 5.6k
Replace Daniel G. Peterson with:
Daniel G. Peterson United States
Andreas Wilm Singapore
Hamish McWilliam United Kingdom
Daniel S. Peterson United States
Daron M. Standley Japan
Alan Filipski United States
Stéphane Guindon France
Chenna Ramu Germany
Heiko A. Schmidt Austria
Olivier Gascuel France
Michael Li relative to Daniel G. Peterson United States Daniel G. Peterson's profile →
Citations per field
00.5×6.5×
Daniel G. Peterson · 1×
Citations per year

Countries citing papers authored by Michael Li

Since Specialization
Citations

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

Fields of papers citing papers by Michael Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20238
3 20237
4 20231
5 20227
6 20229
7 20215
8 202129
9 20213
10 202013
11 20207
12 201950
13 201927
14 20187
15 201856
16
MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms
Hit paper breakdown →
201827005
17 201447
18 2014147
19 201313
20 198317

About Michael Li

Michael Li is a scholar working on Otorhinolaryngology, Aging, Anesthesiology and Pain Medicine, Surgery and Pulmonary and Respiratory Medicine, having authored 30 papers that have together received 28.5k indexed citations. Recurring topics across this work include Reconstructive Surgery and Microvascular Techniques (6 papers), Tracheal and airway disorders (6 papers), Head and Neck Cancer Studies (6 papers), Head and Neck Surgical Oncology (5 papers), Trauma Management and Diagnosis (3 papers), Genomics and Phylogenetic Studies (2 papers), Esophageal Cancer Research and Treatment (2 papers) and Reconstructive Facial Surgery Techniques (2 papers). The work is most often cited by research in Parasitology (1.7k citations), Endocrinology (1.3k citations), Plant Science (8.3k citations), Horticulture (215 citations) and Ecology (5.6k citations). Michael Li has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Sudhir Kumar, Glen Stecher, Koichiro Tamura, Steven Weaver, Stephen D. Shank, Spencer V. Muse, Sergei L. Kosakovsky Pond, Stephanie J. Spielman, Stephen Y. Kang and Michael N. Nitabach. Their work appears in journals such as Oral Oncology, Head & Neck, Annals of Surgical Oncology, Molecular Biology and Evolution and 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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