Lisha Kuang

849 citations
19 papers · 664 indexed · h-index 15
  • Neurology top 5%
    • Amyotrophic Lateral Sclerosis Research 8
  • Genetics top 10%
    • Neurogenetic and Muscular Disorders Research 5
    • RNA Research and Splicing 6
    • Natural product bioactivities and synthesis 3
    • Cancer-related gene regulation 2
    • Glycosylation and Glycoproteins Research 1
    • Amyotrophic Lateral Sclerosis Research 8
    • Phytochemistry and Biological Activities 2
    • Bioactive Compounds and Antitumor Agents 1

Lisha Kuang

18 papers receiving 656 citations

Peers

Lisha Kuang
Comparison fields: 5 of 83
  • Neurology 236
  • Genetics 153
  • Molecular Biology 479
  • Neurology 40
  • Cell Biology 48
Replace Mauricio Budini with:
Mauricio Budini Chile
Raffaella Klima Italy
Azadeh Kia United Kingdom
En‐Ching Luo United States
Xudong Ma China
Hee Soon Choi South Korea
Joo Seok Han South Korea
Jiou Wang United States
Jisen Huai Germany
Saad M. Khan United States
Lisha Kuang relative to Mauricio Budini Chile Mauricio Budini's profile →
Citations per field
00.5×1.5×
Mauricio Budini · 1×
Citations per year

Countries citing papers authored by Lisha Kuang

Since Specialization
Citations

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

Fields of papers citing papers by Lisha Kuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

19 of 19 papers shown
#Work
1 20230
2 202242
3 20209
4 202041
5 202015
6 201916
7 2018128
8 201720
9 2016100
10 201688
11
The proliferative and migratory effects of physical injury and stromal cell-derived factor-1α on rat cardiomyocytes and fibroblasts.
20159
12 201321
13 201232
14 201116
15 201065
16 200926
17 200918
18 200715
19 20073

About Lisha Kuang

Lisha Kuang is a scholar working on Neurology, Genetics and Toxicology, having authored 19 papers that have together received 664 indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (8 papers), RNA Research and Splicing (6 papers), Neurogenetic and Muscular Disorders Research (5 papers), Natural product bioactivities and synthesis (3 papers), Phytochemistry and Biological Activities (2 papers), Cancer-related gene regulation (2 papers), Bioactive Compounds and Antitumor Agents (1 paper) and Glycosylation and Glycoproteins Research (1 paper). The work is most often cited by research in Neurology (236 citations), Genetics (153 citations) and Molecular Biology (479 citations). Lisha Kuang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Haining Zhu, Jing Chen, Edward J. Kasarskis, József Gál, Huan Jin, Min Qian, Kelly R. Barnett, Jianjun Zhai, Bing Du and Lawrence J. Hayward. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Neurochemistry and Human Molecular Genetics.

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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