Jacob G. Scott

5.9k total citations
138 papers, 2.8k citations indexed

About

Jacob G. Scott is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Cancer Research. According to data from OpenAlex, Jacob G. Scott has authored 138 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Pulmonary and Respiratory Medicine, 39 papers in Oncology and 39 papers in Cancer Research. Recurrent topics in Jacob G. Scott's work include Cancer Genomics and Diagnostics (28 papers), Sarcoma Diagnosis and Treatment (26 papers) and Advanced Radiotherapy Techniques (19 papers). Jacob G. Scott is often cited by papers focused on Cancer Genomics and Diagnostics (28 papers), Sarcoma Diagnosis and Treatment (26 papers) and Advanced Radiotherapy Techniques (19 papers). Jacob G. Scott collaborates with scholars based in United States, United Kingdom and Germany. Jacob G. Scott's co-authors include Alexander R.A. Anderson, Andriy Marusyk, Prakash Chinnaiyan, David Basanta, Andrew Dhawan, E. McTyre, Robert A. Gatenby, Daniel Nichol, Adrian L. Harris and Francesca M. Buffa and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Jacob G. Scott

126 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jacob G. Scott United States 31 852 722 704 654 549 138 2.8k
Javier F. Torres–Roca United States 29 963 1.1× 613 0.8× 696 1.0× 938 1.4× 722 1.3× 82 2.7k
Heiko Enderling United States 34 503 0.6× 792 1.1× 840 1.2× 1.4k 2.2× 566 1.0× 118 3.2k
T. E. Wheldon United Kingdom 24 630 0.7× 494 0.7× 388 0.6× 449 0.7× 945 1.7× 87 2.3k
B. I. Lord United Kingdom 31 503 0.6× 1.2k 1.6× 436 0.6× 1.3k 2.0× 621 1.1× 106 4.3k
Michael R. Rossi United States 25 341 0.4× 714 1.0× 368 0.5× 355 0.5× 118 0.2× 76 1.7k
E. Brian Butler United States 35 2.1k 2.4× 792 1.1× 521 0.7× 1.2k 1.8× 842 1.5× 227 4.7k
Stanley K. Liu Canada 35 821 1.0× 1.7k 2.3× 810 1.2× 914 1.4× 361 0.7× 135 4.1k
Ingrid Hofland Netherlands 19 486 0.6× 830 1.1× 545 0.8× 863 1.3× 249 0.5× 36 2.1k
Daniel A. Hamstra United States 36 2.0k 2.3× 1.1k 1.6× 447 0.6× 710 1.1× 1.7k 3.1× 159 5.0k
Niels Halama Germany 32 588 0.7× 1.1k 1.5× 756 1.1× 3.1k 4.7× 1.2k 2.2× 114 5.7k

Countries citing papers authored by Jacob G. Scott

Since Specialization
Citations

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

Fields of papers citing papers by Jacob G. Scott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacob G. Scott. 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 Jacob G. Scott. The network helps show where Jacob G. Scott may publish in the future.

Co-authorship network of co-authors of Jacob G. Scott

This figure shows the co-authorship network connecting the top 25 collaborators of Jacob G. Scott. A scholar is included among the top collaborators of Jacob G. Scott 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 Jacob G. Scott. Jacob G. Scott 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.
Weaver, Davis T., et al.. (2025). Fitness seascapes are necessary for realistic modeling of the evolutionary response to drug therapy. Science Advances. 11(24). eadv1268–eadv1268.
2.
Mohamed, Abdallah, Jacob G. Scott, James E. Bates, et al.. (2025). Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints. Physics and Imaging in Radiation Oncology. 33. 100715–100715.
3.
Hitomi, Masahiro, et al.. (2024). Alamar Blue assay optimization to minimize drug interference and inter assay viability. MethodsX. 13. 103024–103024. 5 indexed citations
4.
Weaver, Davis T., et al.. (2024). Cell-cell fusion in cancer: The next cancer hallmark?. The International Journal of Biochemistry & Cell Biology. 175. 106649–106649. 5 indexed citations
5.
6.
7.
Stephans, Kevin L., et al.. (2024). Spatially Fractionated Radiotherapy (SFRT) for Large Tumors: A Single Institutional Experience of Dosimetry and Clinical Outcomes. International Journal of Radiation Oncology*Biology*Physics. 120(2). e425–e426. 1 indexed citations
8.
Torres–Roca, Javier F., G. Daniel Grass, Jacob G. Scott, & Steven A. Eschrich. (2023). Towards Data Driven RT Prescription: Integrating Genomics into RT Clinical Practice. Seminars in Radiation Oncology. 33(3). 221–231. 1 indexed citations
9.
Jia, Xun, Sean Parker, Judit Kocsis, et al.. (2023). Meta-Analysis of Five Fraction Preoperative Radiotherapy for Soft Tissue Sarcoma. International Journal of Radiation Oncology*Biology*Physics. 117(2). S146–S147. 2 indexed citations
10.
Ågren, J. Arvid & Jacob G. Scott. (2023). Viruses, cancers, and evolutionary biology in the clinic: a commentary on Leeks et al. 2023. Journal of Evolutionary Biology. 36(11). 1587–1589.
11.
Somervuo, Panu, J. Arvid Ågren, Juha Kesseli, et al.. (2023). Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems. Journal of Mathematical Biology. 86(5). 68–68. 2 indexed citations
12.
Qi, Peng, Gregory M.M. Videtic, Kevin L. Stephans, et al.. (2023). Clinical Nomogram Using Novel Computed Tomography–Based Radiomics Predicts Survival in Patients With Non–Small-Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy. JCO Clinical Cancer Informatics. 7(7). e2200173–e2200173. 3 indexed citations
13.
Durmaz, Arda & Jacob G. Scott. (2022). Stability of scRNA-Seq Analysis Workflows is Susceptible to Preprocessing and is Mitigated by Regularized or Supervised Approaches. Evolutionary Bioinformatics. 18. 3253684202–3253684202. 2 indexed citations
14.
Scott, Jacob G., Philip K. Maini, Alexander R.A. Anderson, & Alexander G. Fletcher. (2019). Inferring Tumor Proliferative Organization from Phylogenetic Tree Measures in a Computational Model. Systematic Biology. 69(4). 623–637. 8 indexed citations
15.
Dhawan, Andrew, Alessandro Barberis, Enric Domingo, et al.. (2019). Guidelines for using sigQC for systematic evaluation of gene signatures. Nature Protocols. 14(5). 1377–1400. 20 indexed citations
16.
Dhawan, Andrew, Jacob G. Scott, Adrian L. Harris, & Francesca M. Buffa. (2018). Pan-cancer characterisation of microRNA across cancer hallmarks reveals microRNA-mediated downregulation of tumour suppressors. Nature Communications. 9(1). 5228–5228. 102 indexed citations
17.
McFarland, Christopher D., Julia A. Yaglom, Jonathan W. Wojtkowiak, et al.. (2017). The Damaging Effect of Passenger Mutations on Cancer Progression. Cancer Research. 77(18). 4763–4772. 76 indexed citations
18.
Ward, Matthew C., et al.. (2017). Factors Associated With Acute and Chronic Wound Complications in Patients With Soft-Tissue Sarcoma With Long-Term Follow-Up. International Journal of Radiation Oncology*Biology*Physics. 99(2). S77–S78. 1 indexed citations
19.
Zhou, Mu, Jacob G. Scott, Baishali Chaudhury, et al.. (2017). Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches. American Journal of Neuroradiology. 39(2). 208–216. 272 indexed citations
20.
Werner, Benjamin, Jacob G. Scott, Andrea Sottoriva, et al.. (2016). The Cancer Stem Cell Fraction in Hierarchically Organized Tumors Can Be Estimated Using Mathematical Modeling and Patient-Specific Treatment Trajectories. Cancer Research. 76(7). 1705–1713. 42 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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