Peter Shaw

6.1k total citations · 1 hit paper
117 papers, 3.3k citations indexed

About

Peter Shaw is a scholar working on Molecular Biology, Pharmacology and Cancer Research. According to data from OpenAlex, Peter Shaw has authored 117 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 25 papers in Pharmacology and 20 papers in Cancer Research. Recurrent topics in Peter Shaw's work include Pharmacogenetics and Drug Metabolism (24 papers), Osteoarthritis Treatment and Mechanisms (8 papers) and Topic Modeling (7 papers). Peter Shaw is often cited by papers focused on Pharmacogenetics and Drug Metabolism (24 papers), Osteoarthritis Treatment and Mechanisms (8 papers) and Topic Modeling (7 papers). Peter Shaw collaborates with scholars based in United States, China and Australia. Peter Shaw's co-authors include Fei Huang, Faizan Niazi, Xia Han, Tsutomu Shimada, Hiroshi Yamazaki, F. Peter Guengerich, Roy D. Altman, Mathew Nicholls, Milton Adesnik and Judith Bjöhle and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Immunity.

In The Last Decade

Peter Shaw

111 papers receiving 3.3k citations

Hit Papers

Gene expression profiling spares early breast cancer pati... 2005 2026 2012 2019 2005 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts
    2005 613 citations Yudi Pawitan, Judith Bjöhle et al. Breast Cancer Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Shaw United States 27 1.3k 935 582 581 306 117 3.3k
Takayuki Ikezoe Japan 36 2.6k 2.0× 1.0k 1.1× 155 0.3× 584 1.0× 119 0.4× 205 4.8k
Sungyoung Lee South Korea 28 1.2k 1.0× 806 0.9× 163 0.3× 202 0.3× 130 0.4× 163 3.0k
Laurent Corcos France 37 2.0k 1.6× 951 1.0× 954 1.6× 559 1.0× 44 0.1× 105 4.8k
Robert A. Parise United States 30 1.4k 1.1× 1.0k 1.1× 533 0.9× 169 0.3× 103 0.3× 100 3.0k
Shinya Sato Japan 42 2.1k 1.6× 1.0k 1.1× 124 0.2× 1.1k 1.9× 259 0.8× 302 5.4k
Ying Zhou China 30 2.0k 1.6× 357 0.4× 232 0.4× 513 0.9× 87 0.3× 128 3.8k
Seiichi Ishida Japan 24 2.5k 2.0× 1.4k 1.5× 297 0.5× 580 1.0× 41 0.1× 69 3.8k
Yuri Nikolsky United States 34 2.3k 1.8× 622 0.7× 222 0.4× 595 1.0× 46 0.2× 55 3.6k
Siyuan Zheng China 32 2.6k 2.0× 611 0.7× 161 0.3× 946 1.6× 63 0.2× 144 4.4k

Countries citing papers authored by Peter Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Peter Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Shaw. A scholar is included among the top collaborators of Peter Shaw 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 Peter Shaw. Peter Shaw 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.
2.
Li, Guoqiang, Jing Wang, Kena Song, et al.. (2024). Emulation and evaluation of tumor cell combined chemotherapy in isotropic/anisotropic collagen fiber microenvironments. Lab on a Chip. 24(11). 2999–3014. 2 indexed citations
3.
Shaw, Peter, et al.. (2023). COVID-19: The Ethno-Geographic Perspective of Differential Immunity. Vaccines. 11(2). 319–319.
4.
Qiu, Linlu, Peter Shaw, Panupong Pasupat, et al.. (2022). Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing. 9157–9179. 15 indexed citations
5.
6.
Song, Zhengyong, Long Zhang, Xiang Li, et al.. (2022). Assembly of Guanine Crystals as a Low-Polarizing Broadband Multilayer Reflector in a Spider, Phoroncidia rubroargentea. ACS Applied Materials & Interfaces. 14(29). 32982–32993. 7 indexed citations
7.
Shaw, Peter, et al.. (2022). Graph Embedding: A Methodological Survey. 142–148. 2 indexed citations
8.
Shaw, Peter, Sunil Krishnan, Sameep Shetty, et al.. (2021). A Clinical Update on the Prognostic Effect of microRNA Biomarkers for Survival Outcome in Nasopharyngeal Carcinoma: A Systematic Review and Meta-Analysis. Cancers. 13(17). 4369–4369. 11 indexed citations
9.
Abu-Khzam, Faisal N., et al.. (2021). A Greedy Heuristic for Cluster Editing with Vertex Splitting. 38–41. 2 indexed citations
10.
11.
Suhr, Alane, Ming‐Wei Chang, Peter Shaw, & Kenton Lee. (2020). Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing. 8372–8388. 39 indexed citations
12.
Nicholls, Mathew, Peter Shaw, Faizan Niazi, Mohit Bhandari, & Asheesh Bedi. (2018). The Impact of Excluding Patients with End-Stage Knee Disease in Intra-Articular Hyaluronic Acid Trials: A Systematic Review and Meta-Analysis. Advances in Therapy. 36(1). 147–161. 30 indexed citations
13.
Concoff, Andrew L., Parag Sancheti, Faizan Niazi, Peter Shaw, & Jeffrey Rosen. (2017). The efficacy of multiple versus single hyaluronic acid injections: a systematic review and meta-analysis. BMC Musculoskeletal Disorders. 18(1). 542–542. 64 indexed citations
14.
Abu-Khzam, Faisal N., et al.. (2015). On the parameterized complexity of dynamic problems. Theoretical Computer Science. 607. 426–434. 7 indexed citations
15.
Huang, Fei, Karen A. Reeves, Xia Han, et al.. (2007). Identification of Candidate Molecular Markers Predicting Sensitivity in Solid Tumors to Dasatinib: Rationale for Patient Selection. Cancer Research. 67(5). 2226–2238. 274 indexed citations
16.
Langston, Michael A., et al.. (2006). The Cluster Editing Problem: Implementations And Experiments. Carleton University's Institutional Repository (MacOdrum Library, Carleton University). 3 indexed citations
17.
Pawitan, Yudi, Judith Bjöhle, Lukas C. Amler, et al.. (2005). Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Research. 7(6). R953–64. 613 indexed citations breakdown →
18.
Gent, Ian P., Ewan MacIntyre, Patrick Prosser, Peter Shaw, & Toby Walsh. (1997). The Constrainedness of Arc Consistency. 8 indexed citations
19.
Shaw, Peter, et al.. (1997). Reconstitution Premixes for Assays Using Purified Recombinant Human Cytochrome P450, NADPH-Cytochrome P450 Reductase, and Cytochromeb5. Archives of Biochemistry and Biophysics. 348(1). 107–115. 80 indexed citations
20.
Shaw, Peter, et al.. (1987). Code CRITEX to simulate transient criticality in fissile solutions. Transactions of the American Nuclear Society. 55. 2 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Takayuki Ikezoe Breakdown of academic impact, for papers by Sungyoung Lee Breakdown of academic impact, for papers by Laurent Corcos Breakdown of academic impact, for papers by Robert A. Parise Breakdown of academic impact, for papers by Shinya Sato Breakdown of academic impact, for papers by Ying Zhou Breakdown of academic impact, for papers by Seiichi Ishida Breakdown of academic impact, for papers by Yuri Nikolsky Breakdown of academic impact, for papers by Siyuan Zheng
Rankless by CCL
2026