Chris J Armit
Impact in
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- Renal and related cancers
- Single-cell and spatial transcriptomics
- Developmental Biology and Gene Regulation
- Pluripotent Stem Cells Research
- Biomedical Text Mining and Ontologies
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- Hydrogels: synthesis, properties, applications
Papers in
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- Developmental Biology and Gene Regulation 5
- Renal and related cancers 3
- Biomedical Text Mining and Ontologies 1
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- Research Data Management Practices 2
- Co-authors
- Richard Baldock (12 shared papers)Lorna Richardson (8 shared papers)Carrie Ritchie (1 shared paper)Stewart Graeme Trost (1 shared paper)Wendy J. Brown (1 shared paper)Julie E. Moss (5 shared papers)Bill Hill (5 shared papers)Yiya Yang (4 shared papers)
- Journals
- Development (6 papers)GigaScience (2 papers)Database (2 papers)Mammalian Genome (2 papers)Disease Models & Mechanisms (1 paper)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Chris J Armit
24 papers receiving 842 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 317
- Molecular Medicine 19
- Nephrology 21
- Epidemiology 60
- Genetics 34
Countries citing papers authored by Chris J Armit
This map shows the geographic impact of Chris J Armit'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 Chris J Armit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris J Armit more than expected).
Fields of papers citing papers by Chris J Armit
This network shows the impact of papers produced by Chris J Armit. 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 Chris J Armit. The network helps show where Chris J Armit may publish in the future.
Co-authors
The 25 scholars most cited alongside Chris J Armit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 209 | |
| 2 | 2013 | 121 | |
| 3 | 2013 | 109 | |
| 4 | 2005 | 81 | |
| 5 | 2015 | 70 | |
| 6 | 2020 | 65 | |
| 7 | 2012 | 31 | |
| 8 | 2015 | 30 | |
| 9 | 2017 | 23 | |
| 10 | 2015 | 22 | |
| 11 | 2015 | 14 | |
| 12 | 2015 | 13 | |
| 13 | 2012 | 11 | |
| 14 | 2002 | 9 | |
| 15 | 2017 | 8 | |
| 16 | 2021 | 8 | |
| 17 | 2015 | 6 | |
| 18 | 2019 | 6 | |
| 19 | 2022 | 6 | |
| 20 | 2015 | 5 |
About Chris J Armit
Chris J Armit is a scholar working on Molecular Biology, Information Systems, Molecular Medicine, Oncology and Epidemiology, having authored 25 papers that have together received 857 indexed citations. Recurring topics across this work include Developmental Biology and Gene Regulation (5 papers), Renal and related cancers (3 papers), Research Data Management Practices (2 papers), Biomedical Text Mining and Ontologies (1 paper), Acute Ischemic Stroke Management (1 paper), Hydrogels: synthesis, properties, applications (1 paper) and Cancer-related Molecular Pathways (1 paper). The work is most often cited by research in Molecular Biology (317 citations), Molecular Medicine (19 citations), Nephrology (21 citations), Epidemiology (60 citations) and Genetics (34 citations). Chris J Armit has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Richard Baldock, Lorna Richardson, Carrie Ritchie, Stewart Graeme Trost, Wendy J. Brown, Julie E. Moss, Bill Hill, Yiya Yang, Shanmugasundaram Venkataraman and Peter L. Stevenson. Their work appears in journals such as Development, GigaScience, Database, Mammalian Genome and Disease Models & Mechanisms.
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.