Jennifer M. Johnston

2.2k citations
28 papers · 1.3k indexed · h-index 18

Jennifer M. Johnston

28 papers receiving 1.3k citations

Peers

Jennifer M. Johnston
Comparison fields: 5 of 131
  • Cellular and Molecular Neuroscience 276
  • Biological Psychiatry 34
  • Clinical Psychology 274
  • Molecular Biology 731
  • Behavioral Neuroscience 28
Replace Hui‐Yuan Wu with:
Hui‐Yuan Wu China
Elena Shumay United States
Jeremiah Kelly United Kingdom
Rufus Turner New Zealand
E. Marie Parsons United States
Linda Chang United States
Anna Kirstine Larsen Denmark
Valentina Villa Italy
Lisa Squassante Italy
Bruce M. Altevogt United States
Jennifer M. Johnston relative to Hui‐Yuan Wu China Hui‐Yuan Wu's profile →
Citations per field
00.5×2.7×
Hui‐Yuan Wu · 1×
Citations per year

Countries citing papers authored by Jennifer M. Johnston

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer M. Johnston

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202410
2 202216
3 201817
4 201711
5 2017139
6 201749
7 201554
8 201527
9 20144
10 201420
11 201432
12 201391
13 201316
14 20121
15 201285
16 201163
17 201173
18 200864
19 200818
20 200515

About Jennifer M. Johnston

Jennifer M. Johnston is a scholar working on Cellular and Molecular Neuroscience, Biological Psychiatry and Clinical Psychology, having authored 28 papers that have together received 1.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (12 papers), Lipid Membrane Structure and Behavior (9 papers), Neuropeptides and Animal Physiology (9 papers), Mindfulness and Compassion Interventions (7 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (4 papers), Protein Structure and Dynamics (4 papers), Chemical Synthesis and Analysis (3 papers) and Posttraumatic Stress Disorder Research (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (276 citations), Biological Psychiatry (34 citations) and Clinical Psychology (274 citations). Jennifer M. Johnston has collaborated with scholars based in United States, United Kingdom and Mexico. Frequent co-authors include Marta Filizola, Davide Provasi, Corey Strickland, Mark A. McCoy, Giovanna Scapin, Xiaoyu Yang, Paul Reichert, Ramesh S. Kashi, W.W. Prosise and Hao Wang. Their work appears in journals such as Nature Communications, PLoS ONE and Biochemistry.

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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