Yu‐Ling Shih

2.4k citations
39 papers · 1.9k · h-index 19

Impact in

    • Escherichia coli research studies
  • Genetics top 2%
    • Bacterial Genetics and Biotechnology

Papers in

    • Bacterial Genetics and Biotechnology 20
    • RNA and protein synthesis mechanisms 7
    • Protein Structure and Dynamics 6

Yu‐Ling Shih

39 papers receiving 1.8k citations

Peers

Yu‐Ling Shih
Comparison fields: 5 of 108
  • Endocrinology 255
  • Genetics 1.0k
  • Molecular Biology 1.3k
  • Molecular Medicine 93
  • Ecology 464
Replace Kumaran S. Ramamurthi with:
Kumaran S. Ramamurthi United States
Zonglin Hu United States
R.E. Crossley United States
Stephen G. Addinall United Kingdom
Cynthia A. Hale United States
May Kihara United States
David M. Raskin United States
Imrich Barák Slovakia
Sébastien Pichoff United States
Alexandre W. Bisson‐Filho United States
Yu‐Ling Shih relative to Kumaran S. Ramamurthi United States Kumaran S. Ramamurthi's profile →
Citations per field
00.5×1.5×2.3×
Kumaran S. Ramamurthi · 1×
Citations per year

Countries citing papers authored by Yu‐Ling Shih

Since Specialization
Citations

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

Fields of papers citing papers by Yu‐Ling Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu‐Ling Shih. 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 Yu‐Ling Shih. The network helps show where Yu‐Ling Shih may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003293
2 2005229
3 2006178
4 2001175
5 1998103
6 200295
7 200583
8 200975
9 200975
10 201666
11 200064
12 200149
13 201648
14 201937
15 201136
16 199730
17 201330
18 199927
19 201526
20 201618

About Yu‐Ling Shih

Yu‐Ling Shih is a scholar working on Genetics, Molecular Biology, Ecology, Endocrinology and Plant Science, having authored 39 papers that have together received 1.9k indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (20 papers), Bacteriophages and microbial interactions (11 papers), RNA and protein synthesis mechanisms (7 papers), Escherichia coli research studies (7 papers), Protein Structure and Dynamics (6 papers), Plant Pathogenic Bacteria Studies (5 papers), Legume Nitrogen Fixing Symbiosis (4 papers) and Vibrio bacteria research studies (3 papers). The work is most often cited by research in Endocrinology (255 citations), Genetics (1.0k citations), Molecular Biology (1.3k citations), Molecular Medicine (93 citations) and Ecology (464 citations). Yu‐Ling Shih has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Lawrence Rothfield, Aziz Taghbalout, Xiaoli Fu, Yan Zhang, George P. C. Salmond, Stephen D. Bentley, Ikuro Kawagishi, Stephen Harris, Glenn F. King and Purva Vats. Their work appears in journals such as Molecular Microbiology, Cell, PLoS ONE, Frontiers in Microbiology and Proceedings of the National Academy of Sciences.

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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