Jennifer J. Smith

2.2k citations
28 papers · 1.6k indexed · h-index 20
Topics
Microbial Metabolic Engineering and Bioproduction (9 papers)Bioinformatics and Genomic Networks (8 papers)Peroxisome Proliferator-Activated Receptors (8 papers)

In The Last Decade

Jennifer J. Smith

27 papers receiving 1.6k citations

Peers

Jennifer J. Smith
Comparison fields: 5 of 111
  • Molecular Biology 1.4k
  • Cell Biology 136
  • Epidemiology 120
  • Plant Science 93
  • Physiology 88
Replace Oliver Drews with:
Oliver Drews Germany
Kay Perry United States
Peter Pichler Austria
L.L. David United States
Burghardt Scheibe Germany
Nobuo Maita Japan
Christine Kaufmann Germany
Philip Brownridge United Kingdom
Gary Loughran Ireland
Lynn VerPlank United States
Jennifer J. Smith relative to Oliver Drews Germany Oliver Drews's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jennifer J. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer J. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jennifer J. Smith. 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 Jennifer J. Smith. The network helps show where Jennifer J. Smith may publish in the future.

Co-authorship network of co-authors of Jennifer J. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer J. Smith. A scholar is included among the top collaborators of Jennifer J. Smith 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 Jennifer J. Smith. Jennifer J. Smith 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 9
2 0
3 10
4 37
5 24
6 19
7 344
8 2
9 64
10 187
11 32
12 19
13 24
14 39
15 72
16 8
17 130
18 38
19 89
20 154

About Jennifer J. Smith

Jennifer J. Smith is a scholar working on Equine, Molecular Biology and Internal Medicine, having authored 28 papers that have together received 1.6k indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (9 papers), Bioinformatics and Genomic Networks (8 papers) and Peroxisome Proliferator-Activated Receptors (8 papers). The work is most often cited by research in Molecular Biology (1.4k citations), Biochemistry (87 citations) and Cell Biology (136 citations). Jennifer J. Smith has collaborated with scholars based in United States, Canada and Taiwan. Frequent co-authors include John D. Aitchison, Marcello Marelli, Richard A. Rachubinski, John Boyle, Ramsey A. Saleem, Sarah Killcoyne, Gregory W. Carter, David J. Dilworth, Franco J. Vizeacoumar and Yuen Yi C. Tam. Their work appears in journals such as Nucleic Acids Research, Nature Genetics and Nature Reviews Molecular Cell Biology.

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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