Kevin Heist

530 total citations
18 papers, 401 citations indexed

About

Kevin Heist is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Kevin Heist has authored 18 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 10 papers in Genetics and 4 papers in Oncology. Recurrent topics in Kevin Heist's work include Glioma Diagnosis and Treatment (6 papers), MRI in cancer diagnosis (4 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (4 papers). Kevin Heist is often cited by papers focused on Glioma Diagnosis and Treatment (6 papers), MRI in cancer diagnosis (4 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (4 papers). Kevin Heist collaborates with scholars based in United States, Russia and India. Kevin Heist's co-authors include Craig J. Galbán, Stefanie Galbán, Brian D. Ross, Jean‐Christophe Brisset, Marina Pasca di Magliano, Josette Pierre, Yaqing Zhang, Filip Bednar, Meredith A. Collins and Alnawaz Rehemtulla and has published in prestigious journals such as Nature Communications, PLoS ONE and European Journal of Medicinal Chemistry.

In The Last Decade

Kevin Heist

18 papers receiving 398 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin Heist United States 10 159 147 98 63 57 18 401
Raffaella Albano Italy 6 158 1.0× 130 0.9× 63 0.6× 86 1.4× 73 1.3× 8 366
Abraham Boskovitz United States 7 123 0.8× 84 0.6× 98 1.0× 80 1.3× 127 2.2× 8 352
Jinming Gu United States 5 217 1.4× 214 1.5× 222 2.3× 92 1.5× 39 0.7× 5 422
Christopher Montemagno France 14 196 1.2× 169 1.1× 86 0.9× 92 1.5× 23 0.4× 31 453
Irsan Kooi Netherlands 12 185 1.2× 231 1.6× 48 0.5× 121 1.9× 38 0.7× 15 483
Z Zhu China 7 338 2.1× 135 0.9× 85 0.9× 92 1.5× 35 0.6× 8 432
Ioannis Roxanis United Kingdom 10 187 1.2× 306 2.1× 172 1.8× 61 1.0× 45 0.8× 18 553
Marion Gilormini France 5 169 1.1× 138 0.9× 53 0.5× 93 1.5× 21 0.4× 7 329
María E. González United States 6 113 0.7× 142 1.0× 32 0.3× 61 1.0× 48 0.8× 10 290
Sameer A. Greenall Australia 13 203 1.3× 142 1.0× 37 0.4× 91 1.4× 125 2.2× 22 424

Countries citing papers authored by Kevin Heist

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Heist

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Heist

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Heist. A scholar is included among the top collaborators of Kevin Heist 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 Kevin Heist. Kevin Heist is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Ross, Brian D., Dariya Malyarenko, Kevin Heist, et al.. (2023). Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model. Tomography. 9(2). 552–566. 3 indexed citations
2.
Heist, Kevin, Heang‐Ping Chan, Brian D. Ross, et al.. (2023). Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography. 9(2). 589–602. 4 indexed citations
3.
Heist, Kevin, et al.. (2023). Segmentation of mouse tibia on MRI using deep learning U-Net models. 9351. 97–97. 1 indexed citations
4.
Heist, Kevin, Brock A. Humphries, Johanna M. Buschhaus, et al.. (2022). Multiparametric MRI to quantify disease and treatment response in mice with myeloproliferative neoplasms. JCI Insight. 7(19). 9 indexed citations
5.
Ross, Brian D., Youngsoon Jang, Kevin Heist, et al.. (2022). A lymphatic-absorbed multi-targeted kinase inhibitor for myelofibrosis therapy. Nature Communications. 13(1). 4730–4730. 11 indexed citations
6.
Dort, Marcian E. Van, Youngsoon Jang, Kevin Heist, et al.. (2021). Structural effects of morpholine replacement in ZSTK474 on Class I PI3K isoform inhibition: Development of novel MEK/PI3K bifunctional inhibitors. European Journal of Medicinal Chemistry. 229. 113996–113996. 8 indexed citations
7.
Li, Yinghua, Bo Li, Wei Li, et al.. (2020). Murine models of IDH-wild-type glioblastoma exhibit spatial segregation of tumor initiation and manifestation during evolution. Nature Communications. 11(1). 3669–3669. 34 indexed citations
8.
Galbán, Stefanie, Carlos E. Espinoza, Kevin Heist, et al.. (2017). A Bifunctional MAPK/PI3K Antagonist for Inhibition of Tumor Growth and Metastasis. Molecular Cancer Therapeutics. 16(11). 2340–2350. 15 indexed citations
9.
Galbán, Stefanie, Wajd N. Al‐Holou, Hanxiao Wang, et al.. (2017). MRI-Guided Stereotactic Biopsy of Murine GBM for Spatiotemporal Molecular Genomic Assessment. Tomography. 3(1). 9–15. 4 indexed citations
10.
Chen, Yan, Quan Zhou, Xue Li, et al.. (2017). Ultrasmall Paramagnetic Iron Oxide Nanoprobe Targeting Epidermal Growth Factor Receptor for In Vivo Magnetic Resonance Imaging of Hepatocellular Carcinoma. Bioconjugate Chemistry. 28(11). 2794–2803. 12 indexed citations
12.
Galbán, Craig J., Bing Ma, Dariya Malyarenko, et al.. (2015). Multi-Site Clinical Evaluation of DW-MRI as a Treatment Response Metric for Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy. PLoS ONE. 10(3). e0122151–e0122151. 51 indexed citations
13.
Bowman, Brittany M., Benjamin A. Hoff, Jennifer L. Boes, et al.. (2015). Phosphorylation of FADD by the kinase CK1α promotes KRAS G12D -induced lung cancer. Science Signaling. 8(361). ra9–ra9. 34 indexed citations
14.
Williams, Terence M., Stefanie Galbán, Fei Li, et al.. (2013). DW-MRI as a Predictive Biomarker of Radiosensitization of GBM through Targeted Inhibition of Checkpoint Kinases. Translational Oncology. 6(2). 133–142. 7 indexed citations
15.
Lemasson, Benjamin, Craig J. Galbán, Jennifer L. Boes, et al.. (2013). Diffusion-Weighted MRI as a Biomarker of Tumor Radiation Treatment Response Heterogeneity: A Comparative Study of Whole-Volume Histogram Analysis versus Voxel-Based Functional Diffusion Map Analysis. Translational Oncology. 6(5). 554–561. 18 indexed citations
16.
Miller, Sharon, Kevin Heist, Ying Feng, et al.. (2012). Multimodal Imaging of Growth and Rapamycin-Induced Regression of Colonic Adenomas in Apc Mutation-Dependent Mouse. Translational Oncology. 5(5). 313–320. 6 indexed citations
17.
Galbán, Stefanie, Benjamin Lemasson, Terence M. Williams, et al.. (2012). DW-MRI as a Biomarker to Compare Therapeutic Outcomes in Radiotherapy Regimens Incorporating Temozolomide or Gemcitabine in Glioblastoma. PLoS ONE. 7(4). e35857–e35857. 29 indexed citations
18.
Collins, Meredith A., Jean‐Christophe Brisset, Yaqing Zhang, et al.. (2012). Metastatic Pancreatic Cancer Is Dependent on Oncogenic Kras in Mice. PLoS ONE. 7(12). e49707–e49707. 134 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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