Chris Armit

1.1k citations
19 papers · 440 indexed · h-index 10

Impact in

  • Biophysics top 10%
    • Cell Image Analysis Techniques
    • Pluripotent Stem Cells Research
    • Renal and related cancers
    • Single-cell and spatial transcriptomics
    • Biomedical Text Mining and Ontologies
    • Gene expression and cancer classification

Papers in

    • Biomedical Text Mining and Ontologies 5
    • Single-cell and spatial transcriptomics 4
    • Genetics, Bioinformatics, and Biomedical Research 3
    • Genomics and Phylogenetic Studies 3
    • Renal and related cancers 3
    • Epigenetics and DNA Methylation 3
    • Cell Image Analysis Techniques 5

Chris Armit

19 papers receiving 435 citations

Peers

Chris Armit
Comparison fields: 5 of 104
  • Biophysics 25
  • Molecular Biology 262
  • Physical Therapy, Sports Therapy and Rehabilitation 13
  • Complementary and alternative medicine 23
  • Biomedical Engineering 88
Replace Douglas R. Lazzaro with:
Douglas R. Lazzaro United States
Annunziata Crupi Italy
Oleg V. Kolomytkin United States
Adrian Gray Australia
Hélène Richard Canada
Barbara J. Muller-Borer United States
Ta‐Ching Chen Taiwan
Jung-Hyun Kim United States
Hooman Khorasani United States
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Citations per field
00.5×10×13×
Douglas R. Lazzaro · 1×
Citations per year

Countries citing papers authored by Chris Armit

Since Specialization
Citations

This map shows the geographic impact of Chris 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 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 Armit more than expected).

Fields of papers citing papers by Chris Armit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2013109
2 2013100
3 200578
4 201228
5 201722
6 201521
7 201515
8 201512
9 20029
10 20129
11 20178
12 20216
13 20195
14 20224
15 20154
16 20154
17 20073
18 20222
19 20151

About Chris Armit

Chris Armit is a scholar working on Molecular Biology, Biophysics, Pulmonary and Respiratory Medicine, Information Systems and Management and Surgery, having authored 19 papers that have together received 440 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (5 papers), Biomedical Text Mining and Ontologies (5 papers), Single-cell and spatial transcriptomics (4 papers), Genetics, Bioinformatics, and Biomedical Research (3 papers), Genomics and Phylogenetic Studies (3 papers), Renal and related cancers (3 papers), Epigenetics and DNA Methylation (3 papers) and Scientific Computing and Data Management (2 papers). The work is most often cited by research in Biophysics (25 citations), Molecular Biology (262 citations), Physical Therapy, Sports Therapy and Rehabilitation (13 citations), Complementary and alternative medicine (23 citations) and Biomedical Engineering (88 citations). Chris Armit has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Richard Baldock, Stewart G. Trost, Wendy J. Brown, Carrie Ritchie, Lorna Richardson, Bill Hill, Yiya Yang, Nick Burton, Shanmugasundaram Venkataraman and Liz Graham. Their work appears in journals such as Development, Mammalian Genome, GigaScience, Database and Nucleic Acids Research.

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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