Jin Su

478 citations
11 papers · 426 · h-index 8

Impact in

Papers in

    • Transgenic Plants and Applications 7
    • CRISPR and Genetic Engineering 2
    • Plant biochemistry and biosynthesis 1
    • Plant Gene Expression Analysis 1

Jin Su

11 papers receiving 421 citations

Peers

Jin Su
Comparison fields: 5 of 54
  • Biotechnology 199
  • Hematology 60
  • Immunology and Allergy 23
  • Immunology 75
  • Molecular Biology 247
Replace Steven Szarka with:
Steven Szarka Canada
Ren‐Huai Huang China
Robert R Haines United States
Marcos Oggero Argentina
Renate R. Scholle South Africa
Julie Couillard Canada
Michael Chang United States
V G Johnson United States
G. I. Pardoe United Kingdom
Esther Schönauer Austria
Jin Su relative to Steven Szarka Canada Steven Szarka's profile →
Citations per field
00.5×4.1×
Steven Szarka · 1×
Citations per year

Countries citing papers authored by Jin Su

Since Specialization
Citations

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

Fields of papers citing papers by Jin Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 2015113
2 201483
3 201758
4 201554
5 201550
6 201632
7
Highly effective expression of glutamine synthetase genes GS1 and GS2 in transgenic rice plants increases nitrogen-deficiency tolerance.
200516
8 200613
9 20044
10 20132
11 20151

About Jin Su

Jin Su is a scholar working on Biotechnology, Molecular Biology, Radiology, Nuclear Medicine and Imaging, Hematology and Immunology, having authored 11 papers that have together received 426 indexed citations. Recurring topics across this work include Transgenic Plants and Applications (7 papers), Hemophilia Treatment and Research (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Immune Cell Function and Interaction (2 papers), CRISPR and Genetic Engineering (2 papers), Trypanosoma species research and implications (1 paper), Plant biochemistry and biosynthesis (1 paper) and Plant Gene Expression Analysis (1 paper). The work is most often cited by research in Biotechnology (199 citations), Hematology (60 citations), Immunology and Allergy (23 citations), Immunology (75 citations) and Molecular Biology (247 citations). Jin Su has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Henry Daniell, Alexandra Sherman, Roland W. Herzog, Xiaomei Wang, Shina Lin, Joey H. Norikane, Stephen J. Streatfield, Liqing Zhu, Phillip A. Doerfler and Barry J. Byrne. Their work appears in journals such as Blood, Plant Biotechnology Journal, Molecular Therapy, Biomaterials and Immunogenetics.

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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