Mi Shi

1.3k citations
24 papers · 876 · h-index 15

Impact in

Papers in

Mi Shi

24 papers receiving 861 citations

Peers

Mi Shi
Comparison fields: 5 of 67
  • Endocrine and Autonomic Systems 407
  • Aging 87
  • Plant Science 411
  • Cellular and Molecular Neuroscience 165
  • Molecular Biology 391
Replace Axel Diernfellner with:
Axel Diernfellner Germany
Tobias Schafmeier Germany
Guocun Huang United States
Audrey S. Howell United States
Weifei Luo United States
Kathryn D. Curtin United States
Zdravko Dragovic Germany
Marla Abodeely United States
Ana Depetris-Chauvin Germany
I. Martha Skerrett United States
Mi Shi relative to Axel Diernfellner Germany Axel Diernfellner's profile →
Citations per field
00.5×1.5×
Axel Diernfellner · 1×
Citations per year

Countries citing papers authored by Mi Shi

Since Specialization
Citations

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

Fields of papers citing papers by Mi Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007153
2 2009106
3 201478
4 200974
5 200774
6 201964
7 200853
8 200653
9 202037
10 202131
11 201527
12 200726
13 201825
14 200721
15 201219
16 200412
17
Effect of F209S Mutation of Escherichia coli AroG on Resistance to Phenylalanine Feedback Inhibition.
200010
18 20054
19 20172
20 20182

About Mi Shi

Mi Shi is a scholar working on Molecular Biology, Endocrine and Autonomic Systems, Plant Science, Cellular and Molecular Neuroscience and Genetics, having authored 24 papers that have together received 876 indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (12 papers), Light effects on plants (8 papers), Plant Molecular Biology Research (3 papers), Photoreceptor and optogenetics research (3 papers), Ubiquitin and proteasome pathways (2 papers), Cancer Genomics and Diagnostics (2 papers), Fungal and yeast genetics research (2 papers) and Photosynthetic Processes and Mechanisms (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (407 citations), Aging (87 citations), Plant Science (411 citations), Cellular and Molecular Neuroscience (165 citations) and Molecular Biology (391 citations). Mi Shi has collaborated with scholars based in United States, China and Norway. Frequent co-authors include Jay Dunlap, Jennifer Loros, Luis Larrondo, William J. Belden, Arun Mehra, Hildur V. Colot, Christopher L. Baker, Allan C. Froehlich, Amita Sehgal and Chen‐Hui Chen. Their work appears in journals such as Cold Spring Harbor Symposia on Quantitative Biology, PLoS Computational Biology, Genetics, Scientific Reports and eLife.

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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