Michelle M. Li

40 total papers · 859 total citations
12 papers, 336 citations indexed

About

Michelle M. Li is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Michelle M. Li has authored 12 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Michelle M. Li's work include Advanced Graph Neural Networks (3 papers), Computational Drug Discovery Methods (3 papers) and Biomedical Text Mining and Ontologies (2 papers). Michelle M. Li is often cited by papers focused on Advanced Graph Neural Networks (3 papers), Computational Drug Discovery Methods (3 papers) and Biomedical Text Mining and Ontologies (2 papers). Michelle M. Li collaborates with scholars based in United States, Switzerland and Singapore. Michelle M. Li's co-authors include Marinka Žitnik, Kexin Huang, Ami S. Bhatt, Stephen B. Montgomery, Matthew G. Durrant, Benjamin A. Siranosian, Ayush Noori, Emily Alsentzer, Man Liang and Ruth Johnson and has published in prestigious journals such as Nature Communications, Bioinformatics and Nature Methods.

In The Last Decade

Michelle M. Li

12 papers receiving 332 citations

Hit Papers

Graph representation lear... 2022 2026 2023 2024 2022 40 80 120

Author Peers

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

Author Last Decade Papers Cites
Michelle M. Li 147 75 55 50 35 12 336
David A. Clifton 226 1.5× 22 0.3× 76 1.4× 20 0.4× 38 1.1× 12 387
Dongsheng Che 250 1.7× 51 0.7× 12 0.2× 55 1.1× 34 1.0× 31 366
Andréa Pinna 156 1.1× 40 0.5× 8 0.1× 46 0.9× 12 0.3× 39 376
Steven R. Ness 155 1.1× 27 0.4× 70 1.3× 16 0.3× 21 0.6× 21 349
Marı́a Dolores Cima-Cabal 131 0.9× 11 0.1× 12 0.2× 22 0.4× 44 1.3× 19 395
Aline Cuénod 118 0.8× 13 0.2× 52 0.9× 35 0.7× 8 0.2× 15 309
Michael Meier 31 0.2× 88 1.2× 44 0.8× 18 0.4× 15 0.4× 38 376
C. K. D. Breek 247 1.7× 12 0.2× 39 0.7× 47 0.9× 20 0.6× 7 333
Chengkai Zhu 196 1.3× 23 0.3× 20 0.4× 50 1.0× 7 0.2× 19 368
Ariane Khaledi 262 1.8× 5 0.1× 165 3.0× 70 1.4× 19 0.5× 9 378

Countries citing papers authored by Michelle M. Li

Since Specialization
Citations

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

Fields of papers citing papers by Michelle M. Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelle M. Li

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle M. Li. A scholar is included among the top collaborators of Michelle M. Li 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 Michelle M. Li. Michelle M. Li 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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