Connie Le

1.0k citations
22 papers · 713 · 1 hit paper · h-index 10

Impact in

Papers in

    • Advanced biosensing and bioanalysis techniques 3
    • CRISPR and Genetic Engineering 3
    • RNA Interference and Gene Delivery 2
    • Infectious Diseases and Tuberculosis 2

Connie Le

19 papers receiving 696 citations

Connie Le's Hit Papers

CRISPR technology incorporating amplification strategies: molecular assays for nucleic acids, proteins, and small molecules 2021 · 232 citations
2320+1+3Years since publication50100150200

Peers

Connie Le
Comparison fields: 5 of 91
  • Infectious Diseases 264
  • Biomedical Engineering 311
  • Molecular Biology 480
  • Business and International Management 13
  • Hepatology 21
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Connie Le relative to Rebecca Ward United States Rebecca Ward's profile →
Citations per field
00.5×6.5×
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Citations per year

Countries citing papers authored by Connie Le

Since Specialization
Citations

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

Fields of papers citing papers by Connie Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020296
2
CRISPR technology incorporating amplification strategies: molecular assays for nucleic acids, proteins, and small molecules
Hit paper breakdown →
2021232
3 202029
4 202028
5 201520
6 201619
7 200916
8 201215
9 202110
10 202110
11 20058
12 20108
13 20126
14 20096
15 20174
16 20083
17 20101
18 20241
19 20221
20 20250

About Connie Le

Connie Le is a scholar working on Molecular Biology, Surgery, Epidemiology, Cardiology and Cardiovascular Medicine and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 713 indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (3 papers), Hepatitis B Virus Studies (3 papers), CRISPR and Genetic Engineering (3 papers), Eosinophilic Disorders and Syndromes (2 papers), Infectious Diseases and Tuberculosis (2 papers), RNA Interference and Gene Delivery (2 papers), Biosensors and Analytical Detection (2 papers) and Urticaria and Related Conditions (1 paper). The work is most often cited by research in Infectious Diseases (264 citations), Biomedical Engineering (311 citations), Molecular Biology (480 citations), Business and International Management (13 citations) and Hepatology (21 citations). Connie Le has collaborated with scholars based in Canada, United States and China. Frequent co-authors include X. Chris Le, D. Lorne Tyrrell, Jinjun Wu, Hongquan Zhang, Hanyong Peng, Jeffrey Tao, Wei Feng, Ashley M. Newbigging, Bo Pang and Yiren Cao. Their work appears in journals such as Analytical Chemistry, Scientific Reports, Journal of Applied Clinical Medical Physics, Analytica Chimica Acta and Drug Discovery Today.

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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