Conor M. Stack

790 citations
10 papers · 653 · h-index 9

Impact in

Papers in

Conor M. Stack

10 papers receiving 641 citations

Peers

Conor M. Stack
Comparison fields: 5 of 67
  • Sensory Systems 292
  • Cellular and Molecular Neuroscience 401
  • Developmental Neuroscience 46
  • Genetics 102
  • Nutrition and Dietetics 117
Replace Daniela Brunert with:
Daniela Brunert Germany
Tan Pongstaporn United States
T. Moriizumi Japan
Leslie K. Sprunger United States
Diana M. Cummings United States
Eric S. Tucker United States
Burak Tepe United States
Robin F. Krimm United States
Marion Richard France
A. Rory McQuiston United States
Conor M. Stack relative to Daniela Brunert Germany Daniela Brunert's profile →
Citations per field
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Daniela Brunert · 1×
Citations per year

Countries citing papers authored by Conor M. Stack

Since Specialization
Citations

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

Fields of papers citing papers by Conor M. Stack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 2009177
2 2006122
3 200682
4 200671
5 200658
6 200845
7 201638
8 200829
9 200728
10 20243

About Conor M. Stack

Conor M. Stack is a scholar working on Cellular and Molecular Neuroscience, Sensory Systems, Nutrition and Dietetics, Molecular Biology and Social Psychology, having authored 10 papers that have together received 653 indexed citations. Recurring topics across this work include Neurobiology and Insect Physiology Research (4 papers), Olfactory and Sensory Function Studies (4 papers), Biochemical Analysis and Sensing Techniques (4 papers), Neuropeptides and Animal Physiology (3 papers), Muscle Physiology and Disorders (2 papers), Neuroendocrine regulation and behavior (2 papers), Genetic Neurodegenerative Diseases (2 papers) and Hypothalamic control of reproductive hormones (1 paper). The work is most often cited by research in Sensory Systems (292 citations), Cellular and Molecular Neuroscience (401 citations), Developmental Neuroscience (46 citations), Genetics (102 citations) and Nutrition and Dietetics (117 citations). Conor M. Stack has collaborated with scholars based in United States, Israel and Italy. Frequent co-authors include Nathalie Mandairon, Christiane Linster, Carly Kiselycznyk, Casara Jean Ferretti, Thomas A. Cleland, Daniel B. Rubin, Maria Pennuto, Kenneth H. Fischbeck, Lingling Kong and Hiroaki Adachi. Their work appears in journals such as Experimental Neurology, Journal of Molecular Neuroscience, Physiology & Behavior, Neuron and European Journal of Neuroscience.

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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