Kiley Graim
Impact in
- Health Informatics top 10%
-
- Cancer Genomics and Diagnostics
- MicroRNA in disease regulation
Papers in
-
- Gene expression and cancer classification 3
- Bioinformatics and Genomic Networks 3
- Genomics and Phylogenetic Studies 3
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- Veterinary Oncology Research 3
- Co-authors
- Zachary Greenberg (2 shared papers)Mei He (2 shared papers)Artem Sokolov (3 shared papers)Joshua M. Stuart (5 shared papers)Yulia Newton (3 shared papers)Robert Baertsch (1 shared paper)Vladislav Uzunangelov (1 shared paper)Donghui Cheng (1 shared paper)
- Journals
- Cancer Research (2 papers)Shock (2 papers)Nature Communications (1 paper)npj Precision Oncology (1 paper)Genome Research (1 paper)
- Partner nations
- United StatesNorwaySwitzerland
In The Last Decade
Kiley Graim
20 papers receiving 510 citations
Peers
Comparison fields: 5 of 97
- Health Informatics 14
- Cancer Research 98
- Pulmonary and Respiratory Medicine 126
- Ecological Modeling 16
- Molecular Biology 241
Countries citing papers authored by Kiley Graim
This map shows the geographic impact of Kiley Graim'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 Kiley Graim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kiley Graim more than expected).
Fields of papers citing papers by Kiley Graim
This network shows the impact of papers produced by Kiley Graim. 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 Kiley Graim. The network helps show where Kiley Graim may publish in the future.
Co-authors
The 25 scholars most cited alongside Kiley Graim, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 149 | |
| 2 | 2023 | 92 | |
| 3 | 2018 | 78 | |
| 4 | 2013 | 48 | |
| 5 | 2017 | 44 | |
| 6 | 2024 | 31 | |
| 7 | 2022 | 12 | |
| 8 | 2020 | 12 | |
| 9 | 2018 | 12 | |
| 10 | 2025 | 11 | |
| 11 | 2017 | 10 | |
| 12 | 2017 | 8 | |
| 13 | 2024 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2024 | 5 | |
| 16 | 2025 | 5 | |
| 17 | 2024 | 3 | |
| 18 | 2022 | 2 | |
| 19 | 2025 | 1 | |
| 20 | 2020 | 1 |
About Kiley Graim
Kiley Graim is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Artificial Intelligence, Genetics and Cancer Research, having authored 21 papers that have together received 539 indexed citations. Recurring topics across this work include Gene expression and cancer classification (3 papers), Machine Learning in Healthcare (3 papers), Veterinary Oncology Research (3 papers), Sepsis Diagnosis and Treatment (3 papers), Bioinformatics and Genomic Networks (3 papers), Genomics and Phylogenetic Studies (3 papers), Cancer Genomics and Diagnostics (2 papers) and Human-Animal Interaction Studies (2 papers). The work is most often cited by research in Health Informatics (14 citations), Cancer Research (98 citations), Pulmonary and Respiratory Medicine (126 citations), Ecological Modeling (16 citations) and Molecular Biology (241 citations). Kiley Graim has collaborated with scholars based in United States, Norway and Switzerland. Frequent co-authors include Zachary Greenberg, Mei He, Artem Sokolov, Joshua M. Stuart, Yulia Newton, Robert Baertsch, Vladislav Uzunangelov, Donghui Cheng, B. Smith and Owen N. Witte. Their work appears in journals such as Cancer Research, Shock, Nature Communications, npj Precision Oncology and Genome 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.