Tessa Campbell

562 citations
25 papers · 424 indexed · h-index 11

Tessa Campbell

24 papers receiving 412 citations

Peers

Tessa Campbell
Comparison fields: 5 of 87
  • Molecular Biology 250
  • Cell Biology 117
  • Physiology 102
  • Cellular and Molecular Neuroscience 84
  • Genetics 38
Replace N. T. Hang Pham with:
N. T. Hang Pham Canada
Joel Wellbourne-Wood Switzerland
Melanie Freeman United States
Jonathan Nardozzi United States
Brant M. Webster United States
Nelly Gareil France
Sara K. Donnelly United States
Naomi Geller Lipsky United States
Dalia Halawani United States
Joshua B. Kelley United States
Tessa Campbell relative to N. T. Hang Pham Canada N. T. Hang Pham's profile →
Citations per field
00.5×2.8×
N. T. Hang Pham · 1×
Citations per year

Countries citing papers authored by Tessa Campbell

Since Specialization
Citations

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

Fields of papers citing papers by Tessa Campbell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tessa Campbell

This figure shows the co-authorship network connecting the top 25 collaborators of Tessa Campbell. A scholar is included among the top collaborators of Tessa Campbell based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tessa Campbell. Tessa Campbell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 1
3 17
4
Medical Education in Global Health: Ethical Considerations
1
5 10
6 13
7 15
8 40
9 49
10 0
11 21
12 23
13 62
14
RNA interference: past, present and future.
49
15
HIV TAT variants differentially influence the production of glucocerebrosidase in Sf9 cells.
5
16
Knockdown of chimeric glucocerebrosidase by green fluorescent protein-directed small interfering RNA.
8
17
Glucocerebrosidase expression and analysis
1
18
Approaches to library screening.
5
19 7
20 9

About Tessa Campbell

Tessa Campbell is a scholar working on Internal Medicine, Cell Biology and Developmental Neuroscience, having authored 25 papers that have together received 424 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Glycosylation and Glycoproteins Research (3 papers) and RNA Interference and Gene Delivery (3 papers). The work is most often cited by research in Cell Biology (117 citations), Cellular and Molecular Neuroscience (84 citations) and Physiology (102 citations). Tessa Campbell has collaborated with scholars based in Canada, United States and Hong Kong. Frequent co-authors include Francis Y.M. Choy, Stephen M. Robbins, Michael Natochin, Shahid Hameed, Janice E.A. Braun, Nikolai O. Artemyev, Mayi Arcellana‐Panlilio, Patrick Ferreira, Weimin Zhang and Huiping Shi. Their work appears in journals such as Journal of Biological Chemistry, Analytical Biochemistry and Biochemical and Biophysical Research Communications.

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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