Jin Sha

3.9k citations
5 papers · 116 · h-index 4

Impact in

    • Retinal Diseases and Treatments
    • Virus-based gene therapy research
    • Genetic Associations and Epidemiology

Papers in

    • Bioinformatics and Genomic Networks 2
    • Retinal Development and Disorders 1
    • Natural product bioactivities and synthesis 1
    • Genetic Associations and Epidemiology 2
    • Virus-based gene therapy research 1

Jin Sha

5 papers receiving 115 citations

Peers

Jin Sha
Comparison fields: 5 of 43
  • Ophthalmology 16
  • Genetics 37
  • Molecular Biology 83
  • Cellular and Molecular Neuroscience 14
  • Pharmacology 6
Replace Puthiya M. Gopinath with:
Puthiya M. Gopinath India
Zihua Liu China
Siying Lin United Kingdom
Shuqin Cao Norway
Tim Scheurenbrand Germany
Guenther Rudolph Germany
Tomoe Yamashita Japan
Yiming Wu China
Kola George United States
Mary‐Louise Freckmann Australia
Jin Sha relative to Puthiya M. Gopinath India Puthiya M. Gopinath's profile →
Citations per field
00.5×1.5×2.4×
Puthiya M. Gopinath · 1×
Citations per year

Countries citing papers authored by Jin Sha

Since Specialization
Citations

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

Fields of papers citing papers by Jin Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

5 of 5 papers shown
#Work
1 201762
2 202124
3 202121
4 20178
5 20201

About Jin Sha

Jin Sha is a scholar working on Molecular Biology, Genetics, Physiology, Endocrinology, Diabetes and Metabolism and Plant Science, having authored 5 papers that have together received 116 indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (2 papers), Bioinformatics and Genomic Networks (2 papers), Genetic Associations and Epidemiology (2 papers), Natural Antidiabetic Agents Studies (1 paper), Phytochemistry and Biological Activities (1 paper), Retinal Development and Disorders (1 paper), Natural product bioactivities and synthesis (1 paper) and Virus-based gene therapy research (1 paper). The work is most often cited by research in Ophthalmology (16 citations), Genetics (37 citations), Molecular Biology (83 citations), Cellular and Molecular Neuroscience (14 citations) and Pharmacology (6 citations). Jin Sha has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Mychajlo S. Kosyk, Valérie Dufour, Artur V. Cideciyan, C. Douglas Witherspoon, Yingbin Shen, Małgorzata Świder, Gustavo D. Aguirre, William W. Hauswirth, John Alexander and Sanford L. Boye. Their work appears in journals such as Pharmacogenomics, Food Science & Nutrition, Translational Psychiatry, Molecular Therapy and Alzheimer s & Dementia.

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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