Thomas Préat

9.8k citations
96 papers · 6.0k indexed · 2 hit papers · h-index 41

Impact in

Papers in

Thomas Préat

94 papers receiving 5.9k citations

Hit Papers

A subset of dopamine neurons signals reward for odour memory in Drosophila 2012 · 402 citations
4021994202620042015200400600

Peers

Thomas Préat
Comparison fields: 5 of 131
  • Cellular and Molecular Neuroscience 4.0k
  • Aging 312
  • Endocrine and Autonomic Systems 573
  • Insect Science 869
  • Genetics 1.7k
Replace J. Douglas Armstrong with:
J. Douglas Armstrong United Kingdom
Hiromu Tanimoto Japan
Scott Waddell United Kingdom
Ann‐Shyn Chiang Taiwan
Jay Hirsh United States
Toshihiro Kitamoto United States
Erich Buchner Germany
Benjamin H. White United States
Daisuke Yamamoto Japan
William G. Quinn United States
Thomas Préat relative to J. Douglas Armstrong United Kingdom J. Douglas Armstrong's profile →
Citations per field
00.5×1.5×
J. Douglas Armstrong · 1×
Citations per year

Countries citing papers authored by Thomas Préat

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Préat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20244
2 20249
3 20238
4 202312
5 201928
6 201616
7 201510
8 2014164
9 2013135
10 201223
11 201013
12 200944
13 200667
14 2004219
15 2004170
16 2001284
17 200129
18 200097
19
Genetic dissection of consolidated memory in Drosophila
Hit paper breakdown →
1994739
20 1993110

About Thomas Préat

Thomas Préat is a scholar working on Cellular and Molecular Neuroscience, Aging, Immunology, Cell Biology and Ecology, Evolution, Behavior and Systematics, having authored 96 papers that have together received 6.0k indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (64 papers), Invertebrate Immune Response Mechanisms (17 papers), Insect and Arachnid Ecology and Behavior (15 papers), Animal Behavior and Reproduction (14 papers), Physiological and biochemical adaptations (11 papers), Developmental Biology and Gene Regulation (11 papers), Cholinesterase and Neurodegenerative Diseases (10 papers) and Insect Utilization and Effects (7 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (4.0k citations), Aging (312 citations), Endocrine and Autonomic Systems (573 citations), Insect Science (869 citations) and Genetics (1.7k citations). Thomas Préat has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Alberto Pascual, Pierre-Yves Plaçais, Tim Tully, Maria Del Vecchio, Guillaume Isabel, P. Tchénio, Séverine Trannoy, Hiromu Tanimoto, Yoshinori Aso and Jean‐Maurice Dura. Their work appears in journals such as Journal of Neuroscience, Cell Reports, Nature, Science and Nature 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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