Dongli Song

106 total papers · 2.8k total citations
78 papers, 2.1k citations indexed

About

Dongli Song is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Dongli Song has authored 78 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 31 papers in Pulmonary and Respiratory Medicine and 19 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Dongli Song's work include Neonatal Respiratory Health Research (22 papers), Neonatal and fetal brain pathology (10 papers) and Extracellular vesicles in disease (9 papers). Dongli Song is often cited by papers focused on Neonatal Respiratory Health Research (22 papers), Neonatal and fetal brain pathology (10 papers) and Extracellular vesicles in disease (9 papers). Dongli Song collaborates with scholars based in China, United States and Canada. Dongli Song's co-authors include Xiangdong Wang, Priya Jegatheesan, Balaji Govindaswami, Klaus P. Kohse, Ferid Murad, Robert W. Wrenn, Douglas C. Throckmorton, David H. Munn, Arthur C. Beall and Peter Gruß and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and SHILAP Revista de lepidopterología.

In The Last Decade

Dongli Song

73 papers receiving 2.1k citations

Author Peers

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

Author Last Decade Papers Cites
Dongli Song 771 415 411 367 271 78 2.1k
Maria Tzetis 700 0.9× 410 1.0× 555 1.4× 103 0.3× 281 1.0× 115 2.3k
Muthuvel Jayachandran 738 1.0× 313 0.8× 260 0.6× 393 1.1× 62 0.2× 89 2.8k
Bridget E. Bax 1.1k 1.4× 257 0.6× 304 0.7× 140 0.4× 131 0.5× 69 2.2k
Andong Qiu 1.1k 1.5× 261 0.6× 269 0.7× 176 0.5× 709 2.6× 45 3.0k
Diane Felsen 930 1.2× 253 0.6× 631 1.5× 336 0.9× 193 0.7× 112 3.2k
Sverre O. Lie 703 0.9× 262 0.6× 133 0.3× 444 1.2× 98 0.4× 100 2.2k
Yasuyuki Nagasawa 945 1.2× 148 0.4× 303 0.7× 196 0.5× 136 0.5× 99 2.6k
Csaba Szalai 640 0.8× 208 0.5× 171 0.4× 779 2.1× 128 0.5× 93 2.3k
Daniela Marzioni 916 1.2× 350 0.8× 240 0.6× 426 1.2× 81 0.3× 91 2.4k
M. Daria Haust 486 0.6× 188 0.5× 284 0.7× 216 0.6× 161 0.6× 83 1.8k

Countries citing papers authored by Dongli Song

Since Specialization
Citations

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

Fields of papers citing papers by Dongli Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongli Song

This figure shows the co-authorship network connecting the top 25 collaborators of Dongli Song. A scholar is included among the top collaborators of Dongli Song 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 Dongli Song. Dongli Song 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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2026