Kuo Song

400 citations
14 papers · 277 · h-index 8

Impact in

Papers in

Kuo Song

13 papers receiving 275 citations

Peers

Kuo Song
Comparison fields: 5 of 46
  • Renewable Energy, Sustainability and the Environment 165
  • Molecular Biology 232
  • Ecology 64
  • Ecology, Evolution, Behavior and Systematics 36
  • Environmental Engineering 22
Replace Alexander Makowka with:
Alexander Makowka Germany
John I. Hendry United States
María Santos‐Merino United States
Mary H. Abernathy United States
Yangkai Duan China
Tiago Toscano Selão Singapore
Masakazu Toyoshima Japan
Sébastien Zappa France
Torfinn Sparstad Norway
Nadine Coosemans Belgium
Kuo Song relative to Alexander Makowka Germany Alexander Makowka's profile →
Citations per field
00.5×1.5×1.8×
Alexander Makowka · 1×
Citations per year

Countries citing papers authored by Kuo Song

Since Specialization
Citations

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

Fields of papers citing papers by Kuo Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2016103
2 201842
3 201840
4 202134
5 201614
6 202113
7 201712
8 20228
9 20244
10 20183
11 20242
12 20221
13 20181
14 20250

About Kuo Song

Kuo Song is a scholar working on Molecular Biology, Renewable Energy, Sustainability and the Environment, Ecology, Evolution, Behavior and Systematics, Ecology and Environmental Chemistry, having authored 14 papers that have together received 277 indexed citations. Recurring topics across this work include Photosynthetic Processes and Mechanisms (10 papers), Mitochondrial Function and Pathology (6 papers), Algal biology and biofuel production (5 papers), ATP Synthase and ATPases Research (5 papers), Biocrusts and Microbial Ecology (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Aquatic Ecosystems and Phytoplankton Dynamics (1 paper) and Microbial Metabolites in Food Biotechnology (1 paper). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (165 citations), Molecular Biology (232 citations), Ecology (64 citations), Ecology, Evolution, Behavior and Systematics (36 citations) and Environmental Engineering (22 citations). Kuo Song has collaborated with scholars based in Germany, China and Australia. Frequent co-authors include Xuefeng Lü, Xiaoming Tan, Yajing Liang, Wolfgang R. Hess, Martin Hagemann, Jens Georg, Sandra Maaß, Guodong Luan, Stephan Klähn and Dörte Becher. Their work appears in journals such as Cell Reports, Frontiers in Microbiology, Applied Microbiology and Biotechnology, Microbiology Spectrum and Current Biology.

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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