Mahtab Marker

1.5k total citations
17 papers, 636 citations indexed

About

Mahtab Marker is a scholar working on Cancer Research, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Mahtab Marker has authored 17 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cancer Research, 10 papers in Molecular Biology and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Mahtab Marker's work include Cancer Genomics and Diagnostics (11 papers), Renal cell carcinoma treatment (10 papers) and Renal and related cancers (6 papers). Mahtab Marker is often cited by papers focused on Cancer Genomics and Diagnostics (11 papers), Renal cell carcinoma treatment (10 papers) and Renal and related cancers (6 papers). Mahtab Marker collaborates with scholars based in United States, Germany and Switzerland. Mahtab Marker's co-authors include Robert J. Motzer, Martin H. Voss, A. Ari Hakimi, Parul Patel, Albert Reising, Fengshen Kuo, Timothy A. Chan, James J. Hsieh, Yuan Cheng and Toni K. Choueiri and has published in prestigious journals such as Journal of Clinical Oncology, Blood and The Lancet Oncology.

In The Last Decade

Mahtab Marker

17 papers receiving 630 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mahtab Marker United States 11 412 359 275 232 83 17 636
Michael Kolinsky Canada 13 572 1.4× 182 0.5× 197 0.7× 361 1.6× 16 0.2× 54 824
Tareq Al Baghdadi United States 12 217 0.5× 196 0.5× 175 0.6× 415 1.8× 43 0.5× 35 593
C. Ormazábal Spain 9 85 0.2× 283 0.8× 204 0.7× 159 0.7× 48 0.6× 12 498
Ajia Presnell United States 8 287 0.7× 215 0.6× 133 0.5× 139 0.6× 46 0.6× 9 627
Marissa S. Mattar United States 12 230 0.6× 290 0.8× 175 0.6× 313 1.3× 30 0.4× 22 666
Markus Mayrhofer Sweden 12 176 0.4× 153 0.4× 181 0.7× 101 0.4× 35 0.4× 21 506
Noah Goodman United States 10 275 0.7× 116 0.3× 103 0.4× 381 1.6× 85 1.0× 12 646
János Szőke United States 5 497 1.2× 404 1.1× 265 1.0× 285 1.2× 13 0.2× 7 854
Brett H. Simmons United States 8 151 0.4× 257 0.7× 124 0.5× 201 0.9× 33 0.4× 9 488
S. Sharma United States 11 211 0.5× 335 0.9× 62 0.2× 175 0.8× 52 0.6× 27 554

Countries citing papers authored by Mahtab Marker

Since Specialization
Citations

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

Fields of papers citing papers by Mahtab Marker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahtab Marker

This figure shows the co-authorship network connecting the top 25 collaborators of Mahtab Marker. A scholar is included among the top collaborators of Mahtab Marker 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 Mahtab Marker. Mahtab Marker 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.
Wiggins, Jennifer, Georgina V. Long, Keith T. Flaherty, et al.. (2021). Circulating tumour DNA in patients with advanced melanoma treated with dabrafenib or dabrafenib plus trametinib: a clinical validation study. The Lancet Oncology. 22(3). 370–380. 70 indexed citations
2.
Hakimi, A. Ari, Martin H. Voss, Fengshen Kuo, et al.. (2019). Transcriptomic Profiling of the Tumor Microenvironment Reveals Distinct Subgroups of Clear Cell Renal Cell Cancer: Data from a Randomized Phase III Trial. Cancer Discovery. 9(4). 510–525. 156 indexed citations
3.
Wiggins, Jennifer, Georgina V. Long, Keith T. Flaherty, et al.. (2019). Circulating tumor DNA (ctDNA) kinetics to predict survival in patients (pts) with unresectable or metastatic melanoma treated with dabrafenib (D) or D + trametinib (T).. Journal of Clinical Oncology. 37(15_suppl). 9510–9510. 1 indexed citations
4.
Voss, Martin H., Albert Reising, Yuan Cheng, et al.. (2018). Genomically annotated risk model for advanced renal-cell carcinoma: a retrospective cohort study. The Lancet Oncology. 19(12). 1688–1698. 107 indexed citations
5.
Voss, Martin H., David Chen, Albert Reising, et al.. (2018). PTEN Expression, Not Mutation Status in TSC1, TSC2, or mTOR, Correlates with the Outcome on Everolimus in Patients with Renal Cell Carcinoma Treated on the Randomized RECORD-3 Trial. Clinical Cancer Research. 25(2). 506–514. 29 indexed citations
6.
7.
Knox, Jennifer J., Carlos H. Barrios, T.M. Kim, et al.. (2017). Final overall survival analysis for the phase II RECORD-3 study of first-line everolimus followed by sunitinib versus first-line sunitinib followed by everolimus in metastatic RCC. Annals of Oncology. 28(6). 1339–1345. 84 indexed citations
8.
Vannucchi, Alessandro M., Srđan Verstovšek, Paola Guglielmelli, et al.. (2017). Ruxolitinib reduces JAK2 p.V617F allele burden in patients with polycythemia vera enrolled in the RESPONSE study. Annals of Hematology. 96(7). 1113–1120. 64 indexed citations
9.
Voss, Martin H., David Chen, Mahtab Marker, et al.. (2017). Tumor genomic analysis for 128 renal cell carcinoma (RCC) patients receiving first-line everolimus: Correlation between outcome and mutations status in MTOR, TSC1, and TSC2.. Journal of Clinical Oncology. 35(6_suppl). 484–484. 3 indexed citations
10.
11.
Voss, Martin H., David Chen, Mahtab Marker, et al.. (2016). Circulating biomarkers and outcome from a randomised phase II trial of sunitinib vs everolimus for patients with metastatic renal cell carcinoma. British Journal of Cancer. 114(6). 642–649. 36 indexed citations
12.
Hsieh, James J., David Chen, Patricia Wang, et al.. (2016). Differential overall survival (OS) results in RECORD-3 study based on three distinct mRCC molecular subgroups classified by BAP1 and/or PBRM1 mutations.. Journal of Clinical Oncology. 34(2_suppl). 561–561. 2 indexed citations
13.
Hsieh, James J., David Chen, Patricia Wang, et al.. (2015). Identification of efficacy biomarkers in a large metastatic renal cell carcinoma (mRCC) cohort through next generation sequencing (NGS): Results from RECORD-3.. Journal of Clinical Oncology. 33(15_suppl). 4509–4509. 22 indexed citations
14.
Voss, Martin H., David Chen, Mahtab Marker, et al.. (2014). Identification and validation of predictive biomarkers (BM) for everolimus (EVE) in metastatic renal cell carcinoma: Analysis of 442 patients on RECORD-3.. Journal of Clinical Oncology. 32(15_suppl). 4531–4531. 1 indexed citations
15.
Vujic, Igor, Mahtab Marker, Christian Posch, et al.. (2014). Merkel cell carcinoma: mitoses, expression of Ki‐67 and bcl‐2 correlate with disease progression. Journal of the European Academy of Dermatology and Venereology. 29(3). 542–548. 16 indexed citations
16.
Marker, Mahtab, et al.. (2013). Azithromycin Inhibits Macrophage Tumor Necrosis Factor Secretion in Response to Both Azithromycin-Susceptible and Azithromycin-Resistant Pneumococci. Journal of the Pediatric Infectious Diseases Society. 3(2). 168–171. 3 indexed citations
17.

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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