John Bothos

1.1k total citations
19 papers, 542 citations indexed

About

John Bothos is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cell Biology. According to data from OpenAlex, John Bothos has authored 19 papers receiving a total of 542 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Pulmonary and Respiratory Medicine and 6 papers in Cell Biology. Recurrent topics in John Bothos's work include Microtubule and mitosis dynamics (6 papers), Liver physiology and pathology (5 papers) and Ubiquitin and proteasome pathways (5 papers). John Bothos is often cited by papers focused on Microtubule and mitosis dynamics (6 papers), Liver physiology and pathology (5 papers) and Ubiquitin and proteasome pathways (5 papers). John Bothos collaborates with scholars based in United States, France and Switzerland. John Bothos's co-authors include Thanos D. Halazonetis, Matthew K. Summers, Francis C. Luca, Michelle Ottey, Daniel M. Scolnick, Monica Venere, Premal H. Patel, Amy Peterson, Nikola P. Pavletich and Philip D. Jeffrey and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Oncogene.

In The Last Decade

John Bothos

19 papers receiving 528 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Bothos United States 10 334 252 179 94 59 19 542
Charles P. Xavier United States 8 292 0.9× 72 0.3× 71 0.4× 69 0.7× 35 0.6× 12 396
Sarah Sabir United Kingdom 6 354 1.1× 174 0.7× 163 0.9× 124 1.3× 25 0.4× 6 540
Zongling Ji United Kingdom 12 491 1.5× 53 0.2× 117 0.7× 66 0.7× 110 1.9× 20 596
Dragana Kopanja United States 16 624 1.9× 66 0.3× 230 1.3× 48 0.5× 14 0.2× 20 739
Yun Seong Jeong United States 9 397 1.2× 44 0.2× 147 0.8× 40 0.4× 16 0.3× 17 499
Dejan Maglic United States 13 387 1.2× 125 0.5× 328 1.8× 62 0.7× 5 0.1× 14 640
Po-Chao Chan Taiwan 11 277 0.8× 156 0.6× 50 0.3× 14 0.1× 76 1.3× 13 440
H Fensterer Germany 7 195 0.6× 108 0.4× 155 0.9× 50 0.5× 9 0.2× 9 462
Makoto Nagahara Japan 10 365 1.1× 83 0.3× 136 0.8× 63 0.7× 10 0.2× 17 539

Countries citing papers authored by John Bothos

Since Specialization
Citations

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

Fields of papers citing papers by John Bothos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Bothos

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

All Works

19 of 19 papers shown
1.
Maris, Michael B., Gilles Salles, Won Seog Kim, et al.. (2024). ASCT2-Targeting Antibody-Drug Conjugate MEDI7247 in Adult Patients with Relapsed/Refractory Hematological Malignancies: A First-in-Human, Phase 1 Study. Targeted Oncology. 19(3). 321–332. 4 indexed citations
2.
Bono, Johann S. de, Mark T. Fleming, Judy S. Wang, et al.. (2021). Phase I Study of MEDI3726: A Prostate-Specific Membrane Antigen-Targeted Antibody–Drug Conjugate, in Patients with mCRPC after Failure of Abiraterone or Enzalutamide. Clinical Cancer Research. 27(13). 3602–3609. 33 indexed citations
3.
Martínez‐Martí, Alex, Margarita Majem, Fabrice Barlési, et al.. (2021). LBA42 COAST: An open-label, randomised, phase II platform study of durvalumab alone or in combination with novel agents in patients with locally advanced, unresectable, stage III NSCLC. Annals of Oncology. 32. S1320–S1320. 19 indexed citations
4.
Bono, Johann S. de, Mark T. Fleming, Richard Cathomas, et al.. (2020). MEDI3726, a prostate-specific membrane antigen (PSMA)-targeted antibody-drug conjugate (ADC) in mCRPC after failure of abiraterone or enzalutamide.. Journal of Clinical Oncology. 38(6_suppl). 99–99. 9 indexed citations
5.
Herbst, Roy S., Fabrice Barlési, L. Paz-Ares, et al.. (2019). P1.04-28 COAST: Durvalumab Alone or with Novel Agents for Locally Advanced, Unresectable, Stage III Non-Small Cell Lung Cancer. Journal of Thoracic Oncology. 14(10). S450–S451. 4 indexed citations
6.
7.
Salgia, Ravi, Premal H. Patel, John Bothos, et al.. (2014). Phase I Dose-Escalation Study of Onartuzumab as a Single Agent and in Combination with Bevacizumab in Patients with Advanced Solid Malignancies. Clinical Cancer Research. 20(6). 1666–1675. 56 indexed citations
8.
Yan, Xin, Stephen Eppler, Lisa A. Damico‐Beyer, et al.. (2013). Population pharmacokinetic analysis from phase I and phase II studies of the humanized monovalent antibody, onartuzumab (MetMAb), in patients with advanced solid tumors. The Journal of Clinical Pharmacology. 53(11). 1103–1111. 33 indexed citations
9.
10.
Patel, Premal H., John Bothos, Joe Leigh Simpson, et al.. (2011). Safety data and patterns of progression in met diagnostic subgroups in OAM4558g; A phase II trial evaluating MetMAb in combination with erlotinib in advanced NSCLC.. Journal of Clinical Oncology. 29(15_suppl). 7604–7604. 7 indexed citations
11.
Bai, Shuang, et al.. (2011). Population pharmacokinetic analysis from phase I and phase II studies of the humanized monovalent antibody, MetMAb, in patients with advanced solid tumors.. Journal of Clinical Oncology. 29(15_suppl). 2571–2571. 4 indexed citations
12.
Moss, Rebecca A., John Bothos, Ellen Filvaroff, et al.. (2010). Phase Ib dose-escalation study of MetMAb, a monovalent antagonist antibody to the receptor MET, in combination with bevacizumab in patients with locally advanced or metastatic solid tumors.. Journal of Clinical Oncology. 28(15_suppl). e13050–e13050. 8 indexed citations
13.
14.
Bothos, John, et al.. (2007). Defective in Mitotic Arrest 1/Ring Finger 8 Is a Checkpoint Protein That Antagonizes the Human Mitotic Exit Network. Molecular Cancer Research. 5(12). 1304–1311. 17 indexed citations
15.
Summers, Matthew K., John Bothos, & Thanos D. Halazonetis. (2005). The CHFR mitotic checkpoint protein delays cell cycle progression by excluding Cyclin B1 from the nucleus. Oncogene. 24(16). 2589–2598. 49 indexed citations
16.
Bothos, John, et al.. (2005). Human LATS1 Is a Mitotic Exit Network Kinase. Cancer Research. 65(15). 6568–6575. 106 indexed citations
17.
Stavridi, Elena S., Yentram Huyen, John Bothos, et al.. (2003). Crystal Structure of a Human Mob1 Protein. Structure. 11(9). 1163–1170. 63 indexed citations
18.
Bothos, John, Matthew K. Summers, Monica Venere, Daniel M. Scolnick, & Thanos D. Halazonetis. (2003). The Chfr mitotic checkpoint protein functions with Ubc13-Mms2 to form Lys63-linked polyubiquitin chains. Oncogene. 22(46). 7101–7107. 80 indexed citations
19.
Mariatos, George, John Bothos, Panayotis Zacharatos, et al.. (2003). Inactivating mutations targeting the chfr mitotic checkpoint gene in human lung cancer.. PubMed. 63(21). 7185–9. 40 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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