Bryce K. Allen

2.1k total citations · 2 hit papers
17 papers, 1.2k citations indexed

About

Bryce K. Allen is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Bryce K. Allen has authored 17 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 10 papers in Computational Theory and Mathematics and 2 papers in Oncology. Recurrent topics in Bryce K. Allen's work include Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (9 papers) and Protein Degradation and Inhibitors (7 papers). Bryce K. Allen is often cited by papers focused on Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (9 papers) and Protein Degradation and Inhibitors (7 papers). Bryce K. Allen collaborates with scholars based in United States, Greece and United Kingdom. Bryce K. Allen's co-authors include Woody Sherman, Zoe Cournia, Brian K. Radak, David A. Pearlman, Nagi G. Ayad, Hsu‐Chun Tsai, Charles Lin, Yujun Tao, Tai‐Sung Lee and Darrin M. York and has published in prestigious journals such as Cancer Research, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Bryce K. Allen

17 papers receiving 1.2k citations

Hit Papers

Relative Binding Free Energy Calculations in Drug Discove... 2017 2026 2020 2023 2017 2020 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bryce K. Allen United States 10 931 472 235 145 118 17 1.2k
Giorgio Saladino United Kingdom 21 1.2k 1.3× 329 0.7× 297 1.3× 118 0.8× 73 0.6× 31 1.4k
Michael J. Bodkin United Kingdom 14 683 0.7× 456 1.0× 206 0.9× 85 0.6× 65 0.6× 26 990
António J. M. Ribeiro Portugal 20 933 1.0× 202 0.4× 273 1.2× 237 1.6× 54 0.5× 41 1.5k
Scott D. Bembenek United States 18 725 0.8× 503 1.1× 344 1.5× 231 1.6× 132 1.1× 30 1.4k
David J. Huggins United States 29 1.4k 1.5× 468 1.0× 258 1.1× 215 1.5× 159 1.3× 63 2.2k
Alan P. Graves United States 14 816 0.9× 360 0.8× 189 0.8× 104 0.7× 105 0.9× 21 1.0k
Boris Aguilar United States 14 1.3k 1.4× 291 0.6× 284 1.2× 177 1.2× 174 1.5× 34 1.9k
Irene Nobeli United Kingdom 19 1.1k 1.2× 278 0.6× 247 1.1× 154 1.1× 53 0.4× 42 1.5k
Veerabahu Shanmugasundaram United States 19 766 0.8× 408 0.9× 142 0.6× 137 0.9× 37 0.3× 39 1.2k
K. Brajesh United States 16 725 0.8× 475 1.0× 251 1.1× 139 1.0× 38 0.3× 20 1.1k

Countries citing papers authored by Bryce K. Allen

Since Specialization
Citations

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

Fields of papers citing papers by Bryce K. Allen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryce K. Allen. 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 Bryce K. Allen. The network helps show where Bryce K. Allen may publish in the future.

Co-authorship network of co-authors of Bryce K. Allen

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

All Works

17 of 17 papers shown
1.
Allen, Bryce K., et al.. (2024). Kinome-Wide Virtual Screening by Multi-Task Deep Learning. International Journal of Molecular Sciences. 25(5). 2538–2538. 3 indexed citations
2.
Wu, Zhiyi, David Dotson, Bryce K. Allen, et al.. (2024). alchemlyb: the simple alchemistry library. The Journal of Open Source Software. 9(101). 6934–6934. 6 indexed citations
3.
Mostofian, Barmak, Asghar M. Razavi, Shivam Patel, et al.. (2023). Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods. Journal of Chemical Information and Modeling. 63(17). 5408–5432. 30 indexed citations
4.
Li, Pengfei, Zhijie Li, Yu Wang, et al.. (2021). Precise Binding Free Energy Calculations for Multiple Molecules Using an Optimal Measurement Network of Pairwise Differences. Journal of Chemical Theory and Computation. 18(2). 650–663. 8 indexed citations
5.
Cournia, Zoe, Bryce K. Allen, Thijs Beuming, et al.. (2020). Rigorous Free Energy Simulations in Virtual Screening. Journal of Chemical Information and Modeling. 60(9). 4153–4169. 125 indexed citations
6.
Lee, Tai‐Sung, Bryce K. Allen, Timothy J. Giese, et al.. (2020). Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery. Journal of Chemical Information and Modeling. 60(11). 5595–5623. 247 indexed citations breakdown →
7.
Lee, Tai‐Sung, Zhixiong Lin, Bryce K. Allen, et al.. (2020). Improved Alchemical Free Energy Calculations with Optimized Smoothstep Softcore Potentials. Journal of Chemical Theory and Computation. 16(9). 5512–5525. 44 indexed citations
8.
Mey, Antonia S. J. S., Bryce K. Allen, Hannah E. Bruce Macdonald, et al.. (2019). Best Practices for Alchemical Free Energy Calculations [Article v1.0]. 2(1). 7 indexed citations
9.
Cournia, Zoe, Bryce K. Allen, & Woody Sherman. (2017). Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations. Journal of Chemical Information and Modeling. 57(12). 2911–2937. 545 indexed citations breakdown →
10.
Allen, Bryce K., Saurabh Mehta, S.W. Ember, et al.. (2017). Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations. ACS Omega. 2(8). 4760–4771. 28 indexed citations
11.
Feiglin, Ariel, Bryce K. Allen, Isaac S. Kohane, & Sek Won Kong. (2017). Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders. Cell Systems. 5(2). 140–148.e2. 9 indexed citations
12.
Allen, Bryce K., et al.. (2015). Large-Scale Computational Screening Identifies First in Class Multitarget Inhibitor of EGFR Kinase and BRD4. Scientific Reports. 5(1). 16924–16924. 48 indexed citations
13.
Allen, Bryce K., Saurabh Mehta, Nagi G. Ayad, & Stephan C. Schürer. (2015). Abstract 3690: Ligand- and structure-based virtual screening to discover dual EGFR and BRD4 inhibitors. Cancer Research. 75(15_Supplement). 3690–3690. 1 indexed citations
14.
Allen, Bryce K., Vasileios Stathias, D. Vidović, et al.. (2014). Epigenetic Pathways and Glioblastoma Treatment: Insights From Signaling Cascades. Journal of Cellular Biochemistry. 116(3). 351–363. 25 indexed citations
15.
Pastori, Chiara, Clara Penas, Claude‐Henry Volmar, et al.. (2014). BET bromodomain proteins are required for glioblastoma cell proliferation. Epigenetics. 9(4). 611–620. 113 indexed citations
16.
Allen, Bryce K., Saurabh Mehta, Nagi G. Ayad, & Stephan C. Schürer. (2014). DD-01 * LIGAND- AND STRUCTURE-BASED VIRTUAL SCREENING TO DISCOVER POLYPHARMACOLOGICAL DUAL EGFR AND BRD4 INHIBITORS. Neuro-Oncology. 16(suppl 5). v60–v60. 2 indexed citations
17.
Nussbaum, Herman, et al.. (1977). Management of bone metastasis-multidisciplinary approach.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 4(1). 93–7. 8 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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