Kiley Graim

9.8k total citations
21 papers, 467 citations indexed

About

Kiley Graim is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, Kiley Graim has authored 21 papers receiving a total of 467 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 5 papers in Pulmonary and Respiratory Medicine and 5 papers in Epidemiology. Recurrent topics in Kiley Graim's work include Sepsis Diagnosis and Treatment (5 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). Kiley Graim is often cited by papers focused on Sepsis Diagnosis and Treatment (5 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). Kiley Graim collaborates with scholars based in United States, Norway and Switzerland. Kiley Graim's co-authors include Zachary Greenberg, Mei He, Artem Sokolov, Joshua M. Stuart, Yulia Newton, B. Smith, Robert Baertsch, Colleen Mathis, Donghui Cheng and Vladislav Uzunangelov and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Kiley Graim

18 papers receiving 454 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kiley Graim United States 10 256 137 113 77 68 21 467
Heejoon Chae South Korea 12 321 1.3× 77 0.6× 111 1.0× 54 0.7× 35 0.5× 42 477
Malin Lando Norway 13 319 1.2× 77 0.6× 183 1.6× 90 1.2× 44 0.6× 17 568
Diana Uribe United States 7 338 1.3× 60 0.4× 270 2.4× 225 2.9× 54 0.8× 9 738
Nikolaos Ignatiadis United States 6 298 1.2× 25 0.2× 90 0.8× 122 1.6× 79 1.2× 11 560
Simen Myhre Norway 10 263 1.0× 39 0.3× 191 1.7× 151 2.0× 56 0.8× 13 522
Epifanio Ruiz United States 6 137 0.5× 47 0.3× 178 1.6× 91 1.2× 65 1.0× 6 351
Braden T. Greer United States 9 334 1.3× 65 0.5× 142 1.3× 113 1.5× 80 1.2× 11 571
Christoph Bartenhagen Germany 17 423 1.7× 38 0.3× 264 2.3× 85 1.1× 150 2.2× 28 651
Timon P.H. Buys Canada 12 369 1.4× 155 1.1× 139 1.2× 154 2.0× 69 1.0× 18 635
Adi Zundelevich Israel 10 438 1.7× 78 0.6× 159 1.4× 195 2.5× 138 2.0× 13 701

Countries citing papers authored by Kiley Graim

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Kiley Graim

This figure shows the co-authorship network connecting the top 25 collaborators of Kiley Graim. A scholar is included among the top collaborators of Kiley Graim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kiley Graim. Kiley Graim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Greenberg, Zachary, Andrew Brock, Jinmai Jiang, et al.. (2025). Nanomaterial isolated extracellular vesicles enable high precision identification of tumor biomarkers for pancreatic cancer liquid biopsy. Journal of Nanobiotechnology. 23(1). 467–467. 1 indexed citations
2.
Smith, Leslie, James A. Cahill, Ji‐Hyun Lee, & Kiley Graim. (2025). Equitable machine learning counteracts ancestral bias in precision medicine. Nature Communications. 16(1). 2144–2144. 5 indexed citations
3.
Tanaka, Sébastien, Lauren Page Black, Dawoud Sulaiman, et al.. (2025). IDENTIFYING A SEPSIS SUBPHENOTYPE CHARACTERIZED BY DYSREGULATED LIPOPROTEIN METABOLISM USING A SIMPLIFIED CLINICAL DATA ALGORITHM. Shock. 64(2). 218–225.
4.
Rando, Halie M., Kiley Graim, Greg Hampikian, & Casey S. Greene. (2024). Many direct-to-consumer canine genetic tests can identify the breed of purebred dogs. Journal of the American Veterinary Medical Association. 262(5). 1–8. 4 indexed citations
5.
Black, Lauren Page, Dawoud Sulaiman, Vinitha Jacob, et al.. (2024). Multiomic molecular patterns of lipid dysregulation in a subphenotype of sepsis with higher shock incidence and mortality. Critical Care. 28(1). 431–431.
6.
Sulaiman, Dawoud, Lauren Page Black, Kevin J. Williams, et al.. (2024). Lipidomic changes in a novel sepsis outcome‐based analysis reveals potent pro‐inflammatory and pro‐resolving signaling lipids. Clinical and Translational Science. 17(3). e13745–e13745. 6 indexed citations
7.
Xia, Yuxing, et al.. (2024). The model student: GPT-4 performance on graduate biomedical science exams. Scientific Reports. 14(1). 5670–5670. 27 indexed citations
8.
Cahill, James A., et al.. (2024). Bringing the Genomic Revolution to Comparative Oncology: Human and Dog Cancers. PubMed. 7(1). 107–129.
9.
Greenberg, Zachary, Kiley Graim, & Mei He. (2023). Towards artificial intelligence-enabled extracellular vesicle precision drug delivery. Advanced Drug Delivery Reviews. 199. 114974–114974. 75 indexed citations
10.
Guirgis, Faheem W., Vinitha Jacob, Morgan Henson, et al.. (2023). DHCR7 Expression Predicts Poor Outcomes and Mortality From Sepsis. Critical Care Explorations. 5(6). e0929–e0929. 7 indexed citations
11.
Bandyopadhyay, Sabyasachi, Tyler J. Loftus, Maria-Cecilia Lopez, et al.. (2022). EARLY DIFFERENTIATION BETWEEN SEPSIS AND STERILE INFLAMMATION VIA URINARY GENE SIGNATURES OF METABOLIC DYSREGULATION. Shock. 58(1). 20–27. 2 indexed citations
12.
Seligson, Nathan D., Dexter X. Jin, Julia A. Elvin, et al.. (2022). Drivers of genomic loss of heterozygosity in leiomyosarcoma are distinct from carcinomas. npj Precision Oncology. 6(1). 29–29. 12 indexed citations
13.
Graim, Kiley, David G. Robinson, Nicholas Carriero, et al.. (2020). Modeling molecular development of breast cancer in canine mammary tumors. Genome Research. 31(2). 337–347. 12 indexed citations
14.
Graim, Kiley, David G. Robinson, Nicholas Carriero, et al.. (2020). Abstract 2504: Modeling molecular development of breast cancer in canine mammary tumors. Cancer Research. 80(16_Supplement). 2504–2504. 1 indexed citations
15.
Cahill, James A., Peter D. Heintzman, Kelley Harris, et al.. (2018). Genomic Evidence of Widespread Admixture from Polar Bears into Brown Bears during the Last Ice Age. Molecular Biology and Evolution. 35(5). 1120–1129. 54 indexed citations
16.
Graim, Kiley, Verena Friedl, Kathleen E. Houlahan, & Joshua M. Stuart. (2018). PLATYPUS: A Multiple—View Learning Predictive Framework for Cancer Drug Sensitivity Prediction. PubMed. 24. 136–147. 12 indexed citations
17.
Newton, Yulia, Adam M. Novak, Teresa Swatloski, et al.. (2017). TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal. Cancer Research. 77(21). e111–e114. 41 indexed citations
18.
Paull, Evan, Kiley Graim, Christopher K. Wong, et al.. (2017). Prophetic Granger Causality to infer gene regulatory networks. PLoS ONE. 12(12). e0170340–e0170340. 6 indexed citations
19.
Graim, Kiley, Achal S. Achrol, Evan Paull, et al.. (2017). Revealing cancer subtypes with higher-order correlations applied to imaging and omics data. BMC Medical Genomics. 10(1). 20–20. 10 indexed citations
20.
Sokolov, Artem, et al.. (2013). Combining heterogeneous data sources for accurate functional annotation of proteins. BMC Bioinformatics. 14(S3). S10–S10. 48 indexed citations

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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