Jia Lu

19 papers receiving 500 citations

Peers

Jia Lu
Comparison fields: 5 of 71
  • Cardiology and Cardiovascular Medicine 177
  • Cellular and Molecular Neuroscience 115
  • Molecular Biology 359
  • Developmental Neuroscience 19
  • Cell Biology 49
Replace Meikun Kan-o with:
Meikun Kan-o Japan
J. Hescheler Germany
Dawn H. Catino United States
Amber L. Bowman United States
Sergii Kyrychenko United States
Sean M. Stevens United States
Héctor Sánchez-Iranzo Spain
Alison M. Maggs United Kingdom
Robert S. Dotson United States
Nellie Kalcheva United States
Jia Lu relative to Meikun Kan-o Japan Meikun Kan-o's profile →
Citations per field
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Meikun Kan-o · 1×
Citations per year

Countries citing papers authored by Jia Lu

Since Specialization
Citations

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

Fields of papers citing papers by Jia Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jia Lu, 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 Jia Lu Line = papers co-authored together Jia Lu 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 2011120
2 201279
3 200976
4 201446
5 201438
6 201335
7 201532
8 201431
9 201113
10 20228
11 20207
12 20086
13
Kalirin-7 contributes to type 2 diabetic neuropathic pain via the postsynaptic density-95/N-methyl-D-aspartate receptor 2B-dependent N-methyl-D-aspartate receptor 2B phosphorylation in the spinal cord in rats.
20205
14 20244
15 20243
16 20192
17 20162
18 20251
19 20131
20 20250

About Jia Lu

Jia Lu is a scholar working on Cardiology and Cardiovascular Medicine, Cellular and Molecular Neuroscience, Molecular Biology, Hematology and Discrete Mathematics and Combinatorics, having authored 24 papers that have together received 509 indexed citations. Recurring topics across this work include Congenital heart defects research (4 papers), Pluripotent Stem Cells Research (3 papers), Cardiac electrophysiology and arrhythmias (3 papers), Cardiomyopathy and Myosin Studies (3 papers), CRISPR and Genetic Engineering (2 papers), Ion channel regulation and function (2 papers), Enzyme Production and Characterization (1 paper) and Dialysis and Renal Disease Management (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (177 citations), Cellular and Molecular Neuroscience (115 citations), Molecular Biology (359 citations), Developmental Neuroscience (19 citations) and Cell Biology (49 citations). Jia Lu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Glenn I. Fishman, Mario Delmar, Xianming Lin, Lori L. Isom, Nian Bao Liu, Jie Zhang, JUSTUS M.B. ANUMONWO, Motohiro Nozumi, Michihiro Igarashi and Kosei Takeuchi. Their work appears in journals such as Neuroscience Research, Heart Rhythm, Stem Cell Reports, Agronomy and Cancer Medicine.

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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