William L. Hwang

5.0k total citations · 1 hit paper
65 papers, 2.4k citations indexed

About

William L. Hwang is a scholar working on Oncology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, William L. Hwang has authored 65 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 17 papers in Molecular Biology and 15 papers in Pulmonary and Respiratory Medicine. Recurrent topics in William L. Hwang's work include Cancer Genomics and Diagnostics (10 papers), Pancreatic and Hepatic Oncology Research (8 papers) and Cancer Immunotherapy and Biomarkers (8 papers). William L. Hwang is often cited by papers focused on Cancer Genomics and Diagnostics (10 papers), Pancreatic and Hepatic Oncology Research (8 papers) and Cancer Immunotherapy and Biomarkers (8 papers). William L. Hwang collaborates with scholars based in United States, United Kingdom and Sweden. William L. Hwang's co-authors include Hagan Bayley, Krishnendu Chakrabarty, Matthew A. Holden, Fei Su, Jay S. Loeffler, Trevor J. Royce, Luke Pike, Brandon A. Mahal, Xiaowei Zhuang and Sebastian Deindl and has published in prestigious journals such as Nature, Cell and Journal of the American Chemical Society.

In The Last Decade

William L. Hwang

58 papers receiving 2.3k citations

Hit Papers

Multidisciplinary standards of care and recent progress i... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
William L. Hwang United States 25 797 797 562 532 334 65 2.4k
Jody V. Vykoukal United States 28 1.1k 1.4× 2.0k 2.5× 371 0.7× 1.1k 2.0× 178 0.5× 75 3.7k
Lu Liu China 29 1.1k 1.4× 787 1.0× 495 0.9× 56 0.1× 193 0.6× 94 2.6k
Lishen Zhang China 15 663 0.8× 487 0.6× 489 0.9× 101 0.2× 155 0.5× 30 2.0k
Yang Du China 30 995 1.2× 2.1k 2.6× 497 0.9× 121 0.2× 383 1.1× 128 3.7k
W. French Anderson United States 27 1.3k 1.6× 829 1.0× 735 1.3× 263 0.5× 173 0.5× 55 3.1k
Jong Woo Lee South Korea 33 1.8k 2.2× 242 0.3× 756 1.3× 888 1.7× 455 1.4× 128 3.9k
Peng Guo China 29 1.2k 1.5× 947 1.2× 394 0.7× 109 0.2× 228 0.7× 109 2.8k
Yoshihiro Morita Japan 23 534 0.7× 134 0.2× 276 0.5× 131 0.2× 153 0.5× 95 1.7k
Takahiro Tsuji Japan 23 593 0.7× 165 0.2× 430 0.8× 80 0.2× 298 0.9× 101 1.8k
Dawid Schellingerhout United States 26 425 0.5× 617 0.8× 356 0.6× 59 0.1× 536 1.6× 106 2.5k

Countries citing papers authored by William L. Hwang

Since Specialization
Citations

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

Fields of papers citing papers by William L. Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William L. Hwang. 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 William L. Hwang. The network helps show where William L. Hwang may publish in the future.

Co-authorship network of co-authors of William L. Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of William L. Hwang. A scholar is included among the top collaborators of William L. Hwang 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 William L. Hwang. William L. Hwang 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.
Cui, Yi, et al.. (2025). Integrated spatial morpho-transcriptomics predicts functional traits in pancreatic cancer. Science Advances. 11(42). eadx0632–eadx0632.
2.
Guo, Jimmy A., Kyle E. Evans, Kazuki Takahashi, et al.. (2025). Integrative genomic identification of therapeutic targets for pancreatic cancer. Cell Reports. 44(9). 116191–116191.
3.
4.
Chen, Sophia Y., Heng‐Chung Kung, Kai Chen, et al.. (2024). Targeting heterogeneous tumor microenvironments in pancreatic cancer mouse models of metastasis by TGF-β depletion. JCI Insight. 9(21). 6 indexed citations
5.
Hwang, William L., et al.. (2024). Spatial oncology: Translating contextual biology to the clinic. Cancer Cell. 42(10). 1653–1675. 27 indexed citations
7.
Guo, Jimmy A., Mohammed Alshalalfa, Daniel Y. Kim, et al.. (2022). DNA repair and immune checkpoint blockade response. Cancer Genetics. 264-265. 1–4. 2 indexed citations
8.
Guo, Jimmy A., Hannah I. Hoffman, Stuti G. Shroff, et al.. (2021). Pan-cancer Transcriptomic Predictors of Perineural Invasion Improve Occult Histopathologic Detection. Clinical Cancer Research. 27(10). 2807–2815. 16 indexed citations
9.
Lebow, Emily S., William L. Hwang, Yi Wang, et al.. (2020). Early experience with hippocampal avoidance whole brain radiation therapy and simultaneous integrated boost for brain metastases. Journal of Neuro-Oncology. 148(1). 81–88. 9 indexed citations
10.
Niyazi, Maximilian, Andrzej Niemierko, Harald Paganetti, et al.. (2019). Volumetric and actuarial analysis of brain necrosis in proton therapy using a novel mixture cure model. Radiotherapy and Oncology. 142. 154–161. 27 indexed citations
11.
Lamba, Nayan, William L. Hwang, Daniel W. Kim, et al.. (2019). Atypical Histopathological Features and the Risk of Treatment Failure in Nonmalignant Meningiomas: A Multi-Institutional Analysis. World Neurosurgery. 133. e804–e812. 6 indexed citations
12.
Sanford, Nina N., et al.. (2019). Trimodality therapy for HPV-positive oropharyngeal cancer: A population-based study. Oral Oncology. 98. 28–34. 13 indexed citations
13.
Hwang, William L., Luke Pike, Trevor J. Royce, Brandon A. Mahal, & Jay S. Loeffler. (2018). Safety of combining radiotherapy with immune-checkpoint inhibition. Nature Reviews Clinical Oncology. 15(8). 477–494. 230 indexed citations
14.
Pike, Luke, William L. Hwang, Trevor J. Royce, Nina N. Sanford, & Brandon A. Mahal. (2018). HPV status predicts for improved survival following chemotherapy in metastatic squamous cell carcinoma of the oropharynx. Oral Oncology. 86. 69–74. 3 indexed citations
15.
Hwang, Katie L., William L. Hwang, Marc R. Bussière, & Helen A. Shih. (2017). The role of radiotherapy in the management of high-grade meningiomas. Chinese Clinical Oncology. 6(S1). S5–S5. 25 indexed citations
16.
Hwang, William L., Ariel E. Marciscano, Anat Stemmer‐Rachamimov, et al.. (2015). Correlation of Imaging Characteristics With Histopathological WHO Grade in Meningiomas. International Journal of Radiation Oncology*Biology*Physics. 93(3). E86–E86.
17.
Hwang, William L., Sebastian Deindl, Bryan T. Harada, & Xiaowei Zhuang. (2014). Histone H4 tail mediates allosteric regulation of nucleosome remodelling by linker DNA. Nature. 512(7513). 213–217. 68 indexed citations
18.
Deindl, Sebastian, William L. Hwang, Swetansu K. Hota, et al.. (2013). ISWI Remodelers Slide Nucleosomes with Coordinated Multi-Base-Pair Entry Steps and Single-Base-Pair Exit Steps. Cell. 152(3). 442–452. 121 indexed citations
19.
Maglia, Giovanni, Andrew J. Heron, William L. Hwang, et al.. (2009). Droplet networks with incorporated protein diodes show collective properties. Nature Nanotechnology. 4(7). 437–440. 192 indexed citations
20.
Maglia, Giovanni, Andrew J. Heron, William L. Hwang, et al.. (2009). Electrical Communication In Droplet Interface Bilayers Networks. Biophysical Journal. 96(3). 544a–544a. 1 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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