Lachlan Gray

2.1k citations
50 papers · 1.6k · h-index 25

Impact in

  • Virology top 0.5%
    • HIV Research and Treatment
    • HIV/AIDS Research and Interventions
    • HIV/AIDS drug development and treatment

Papers in

    • HIV Research and Treatment 42
    • HIV/AIDS Research and Interventions 18
    • HIV/AIDS drug development and treatment 16

Lachlan Gray

50 papers receiving 1.6k citations

Peers

Lachlan Gray
Comparison fields: 5 of 99
  • Virology 1.2k
  • Infectious Diseases 662
  • Immunology 535
  • Sensory Systems 111
  • Neurology 171
Replace Dianne M. Rausch with:
Dianne M. Rausch United States
Yonatan Ganor France
Avi Nath United States
Francesca Sironi Italy
Marek Fischer Switzerland
Debbie D. Watry United States
Cory White United States
R Caliò Italy
Eliseo A. Eugenin United States
J. Motte France
Lachlan Gray relative to Dianne M. Rausch United States Dianne M. Rausch's profile →
Citations per field
00.5×10×13.9×
Dianne M. Rausch · 1×
Citations per year

Countries citing papers authored by Lachlan Gray

Since Specialization
Citations

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

Fields of papers citing papers by Lachlan Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010146
2 201094
3 201494
4 200594
5 201189
6 200677
7 200773
8 201360
9 201354
10 201051
11 201451
12 200949
13 201347
14 200641
15 200836
16 201434
17 201234
18 201533
19 201233
20 201029

About Lachlan Gray

Lachlan Gray is a scholar working on Virology, Infectious Diseases, Immunology, Epidemiology and Molecular Biology, having authored 50 papers that have together received 1.6k indexed citations. Recurring topics across this work include HIV Research and Treatment (42 papers), HIV/AIDS Research and Interventions (18 papers), HIV/AIDS drug development and treatment (16 papers), Immune Cell Function and Interaction (15 papers), Cytomegalovirus and herpesvirus research (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), interferon and immune responses (3 papers) and vaccines and immunoinformatics approaches (3 papers). The work is most often cited by research in Virology (1.2k citations), Infectious Diseases (662 citations), Immunology (535 citations), Sensory Systems (111 citations) and Neurology (171 citations). Lachlan Gray has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Melissa J. Churchill, Paul R. Gorry, Steve Wesselingh, Michael Roche, Jasminka Sterjovski, Anne Ellett, Sharon R. Lewin, Anthony L. Cunningham, Daniel Cowley and Bruce J. Brew. Their work appears in journals such as Journal of NeuroVirology, Virology, Journal of Virology, Retrovirology and PLoS ONE.

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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