Jin Támaoka

5.0k citations
25 papers · 4.5k indexed · 2 hit papers · h-index 17
Topics
Microbial Community Ecology and Physiology (8 papers)Genomics and Phylogenetic Studies (8 papers)DNA and Nucleic Acid Chemistry (4 papers)

In The Last Decade

Jin Támaoka

24 papers receiving 4.3k citations

Hit Papers

Determination of DNA base composition by reversed-phase h...19832026199720111984198350010001.5k2.0k

Peers

Jin Támaoka
Comparison fields: 5 of 108
  • Molecular Biology 3.7k
  • Ecology 2.1k
  • Plant Science 806
  • Biotechnology 569
  • Cell Biology 445
Replace USHA PREMACHANDRAN with:
USHA PREMACHANDRAN United States
M.D. Collins United Kingdom
Hiroaki Kasai Japan
Tae-Kwang Oh South Korea
Kyung Sook Bae South Korea
Simon J. Shaw United States
Yu‐Guang Zhou China
Ingrid Groth Germany
Chang‐Jin Kim South Korea
Nadine Ziemert Germany
Jin Támaoka relative to USHA PREMACHANDRAN United States USHA PREMACHANDRAN's profile →
Citations per field
00.5×10×12.8×
USHA PREMACHANDRAN · 1×
Citations per year

Countries citing papers authored by Jin Támaoka

Since Specialization
Citations

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

Fields of papers citing papers by Jin Támaoka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Támaoka

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Támaoka. A scholar is included among the top collaborators of Jin Támaoka 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 Jin Támaoka. Jin Támaoka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 35
3 29
4 72
5 204
6 4
7 191
8 124
9
Determination of DNA Base Composition
111
10 11
11 70
12 16
13 167
14 131
15 52
16 7
17 1
18 190
19
Determination of DNA base composition by reversed-phase high-performance liquid chromatographybreakdown →
2351
20
Analysis of bacterial menaquinone mixtures by high performance liquid chromatographybreakdown →
630

About Jin Támaoka

Jin Támaoka is a scholar working on Filtration and Separation, Environmental Chemistry and Ecology, having authored 25 papers that have together received 4.5k indexed citations. Recurring topics across this work include Microbial Community Ecology and Physiology (8 papers), Genomics and Phylogenetic Studies (8 papers) and DNA and Nucleic Acid Chemistry (4 papers). The work is most often cited by research in Microbiology (211 citations), Ecology (2.1k citations) and Biotechnology (569 citations). Jin Támaoka has collaborated with scholars based in Japan, Germany and United Kingdom. Frequent co-authors include Kazuo Komagata, Yoko Katayama-Fujimura, Hiroshi Kuraishi, Chiaki Kato, Lina Li, Koki Horikoshi, K. Komagata, Teizi Urakami, Yuichi Nogi and Yuka Nakamura. Their work appears in journals such as Applied and Environmental Microbiology, Methods in enzymology on CD-ROM/Methods in enzymology and Plant Physiology and Biochemistry.

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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