Karen Ross

17.7k citations
59 papers · 1.1k indexed · h-index 19
  • Cell Biology top 10%
    • Microtubule and mitosis dynamics 9
    • Biomedical Text Mining and Ontologies 14
    • Bioinformatics and Genomic Networks 14
    • Machine Learning in Bioinformatics 7
    • Genomics and Phylogenetic Studies 7
    • Cancer-related gene regulation 4
    • Fungal and yeast genetics research 4
    • Advanced Proteomics Techniques and Applications 4

Karen Ross

55 papers receiving 1.1k citations

Peers

Karen Ross
Comparison fields: 5 of 124
  • Molecular Medicine 125
  • Cell Biology 190
  • Endocrinology 55
  • Molecular Biology 729
  • Oncology 145
Replace Darcie J. Miller with:
Darcie J. Miller United States
Ricardo Medina United States
S.M. Soisson United States
Andrei Starostine Canada
N. LaRonde-LeBlanc United States
Christian K. Engel Germany
M. Raymond V. Finlay United Kingdom
Mark Ammirati United States
Paola Lo Surdo Italy
Bryan K. Beattie Canada
Karen Ross relative to Darcie J. Miller United States Darcie J. Miller's profile →
Citations per field
00.5×1.5×1.9×
Darcie J. Miller · 1×
Citations per year

Countries citing papers authored by Karen Ross

Since Specialization
Citations

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

Fields of papers citing papers by Karen Ross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20239
3 20230
4 20231
5 20224
6 20220
7 202143
8 202187
9 20219
10 202026
11 201918
12 201823
13 20187
14 20164
15 201617
16 201545
17 20159
18
Knowledge Representation of Protein PTMs and Complexes in the Protein Ontology: Application to Multi-Faceted Disease Analysis
20141
19 200713
20 200449

About Karen Ross

Karen Ross is a scholar working on Cell Biology, Molecular Biology and Molecular Medicine, having authored 59 papers that have together received 1.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (14 papers), Bioinformatics and Genomic Networks (14 papers), Microtubule and mitosis dynamics (9 papers), Machine Learning in Bioinformatics (7 papers), Genomics and Phylogenetic Studies (7 papers), Cancer-related gene regulation (4 papers), Advanced Proteomics Techniques and Applications (4 papers) and Fungal and yeast genetics research (4 papers). The work is most often cited by research in Molecular Medicine (125 citations), Cell Biology (190 citations) and Endocrinology (55 citations). Karen Ross has collaborated with scholars based in United States, Canada and Brazil. Frequent co-authors include Cathy Wu, Orna Cohen‐Fix, Philipp Kaldis, Cecilia N. Arighi, K. Vijay‐Shanker, Aiyang Cheng, Michael J. Solomon, Michaël Chandler, Alessandro M. Varani and Hongzhan Huang. Their work appears in journals such as Nucleic Acids Research, Genes & Development and Bioinformatics.

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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2026