Kay Grennan
Impact in
- Biological Psychiatry top 10%
- Tryptophan and brain disorders
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- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
- RNA Research and Splicing
Papers in
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- Bioinformatics and Genomic Networks 4
- RNA Research and Splicing 2
- Genetics 8
- Genetic Associations and Epidemiology 6
- Genomics and Rare Diseases 2
- Genetic Mapping and Diversity in Plants and Animals 2
- Genomic variations and chromosomal abnormalities 2
- Genetics and Neurodevelopmental Disorders 1
- Co-authors
- Chunyu Liu (9 shared papers)Elliot S. Gershon (7 shared papers)Chao Chen (6 shared papers)Judith A. Badner (2 shared papers)Jin Li (1 shared paper)Dandan Zhang (1 shared paper)Lijun Cheng (2 shared papers)Fabio Pibiri (1 shared paper)
- Journals
- Molecular Psychiatry (4 papers)Dialogues in Clinical Neuroscience (2 papers)BioEssays (1 paper)Science Translational Medicine (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Kay Grennan
11 papers receiving 699 citations
Peers
Comparison fields: 5 of 98
- Biological Psychiatry 41
- Molecular Biology 382
- Cancer Research 74
- Genetics 115
- Behavioral Neuroscience 12
Countries citing papers authored by Kay Grennan
This map shows the geographic impact of Kay Grennan'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 Kay Grennan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kay Grennan more than expected).
Fields of papers citing papers by Kay Grennan
This network shows the impact of papers produced by Kay Grennan. 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 Kay Grennan. The network helps show where Kay Grennan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kay Grennan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 379 | |
| 2 | 2012 | 114 | |
| 3 | 2013 | 91 | |
| 4 | 2018 | 59 | |
| 5 | 2013 | 19 | |
| 6 | 2014 | 17 | |
| 7 | 2014 | 12 | |
| 8 | 2024 | 9 | |
| 9 | 2015 | 4 | |
| 10 | 2020 | 3 | |
| 11 | 2016 | 1 |
About Kay Grennan
Kay Grennan is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Biological Psychiatry, having authored 11 papers that have together received 708 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (6 papers), Bioinformatics and Genomic Networks (4 papers), Genomics and Rare Diseases (2 papers), Genetic Mapping and Diversity in Plants and Animals (2 papers), RNA Research and Splicing (2 papers), Genomic variations and chromosomal abnormalities (2 papers), Pharmacogenetics and Drug Metabolism (1 paper) and Genetics and Neurodevelopmental Disorders (1 paper). The work is most often cited by research in Biological Psychiatry (41 citations), Molecular Biology (382 citations), Cancer Research (74 citations), Genetics (115 citations) and Behavioral Neuroscience (12 citations). Kay Grennan has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Chunyu Liu, Elliot S. Gershon, Chao Chen, Judith A. Badner, Jin Li, Dandan Zhang, Lijun Cheng, Fabio Pibiri, Ney Alliey‐Rodriguez and Joseph J. Cooper. Their work appears in journals such as Molecular Psychiatry, Dialogues in Clinical Neuroscience, BioEssays, Science Translational Medicine and PLoS Computational 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.