Adam Jendrisak

1.6k total citations · 1 hit paper
32 papers, 988 citations indexed

About

Adam Jendrisak is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Adam Jendrisak has authored 32 papers receiving a total of 988 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Oncology, 22 papers in Pulmonary and Respiratory Medicine and 17 papers in Cancer Research. Recurrent topics in Adam Jendrisak's work include Prostate Cancer Treatment and Research (18 papers), Cancer Genomics and Diagnostics (17 papers) and Cancer Cells and Metastasis (16 papers). Adam Jendrisak is often cited by papers focused on Prostate Cancer Treatment and Research (18 papers), Cancer Genomics and Diagnostics (17 papers) and Cancer Cells and Metastasis (16 papers). Adam Jendrisak collaborates with scholars based in United States, United Kingdom and Ireland. Adam Jendrisak's co-authors include Ryan Dittamore, Ryon P. Graf, Jessica Louw, Howard I. Scher, Nicole A. Schreiber, Dena Marrinucci, David Lu, Martin Fleisher, Brigit McLaughlin and Stephanie Greene and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Cancer Research.

In The Last Decade

Adam Jendrisak

29 papers receiving 974 citations

Hit Papers

Association of AR-V7 on Circulating Tumor Cells as a Trea... 2016 2026 2019 2022 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adam Jendrisak United States 10 679 518 510 255 104 32 988
Jessica Louw United States 9 692 1.0× 532 1.0× 479 0.9× 249 1.0× 114 1.1× 30 988
Penelope Flohr United Kingdom 10 771 1.1× 555 1.1× 302 0.6× 439 1.7× 89 0.9× 25 1.1k
Mateus Crespo United Kingdom 17 525 0.8× 393 0.8× 421 0.8× 399 1.6× 97 0.9× 44 1.0k
Wendy Onstenk Netherlands 19 397 0.6× 456 0.9× 455 0.9× 257 1.0× 86 0.8× 25 813
John L. Silberstein United States 12 728 1.1× 323 0.6× 413 0.8× 314 1.2× 126 1.2× 16 1.0k
Aseem Anand United States 17 668 1.0× 313 0.6× 383 0.8× 135 0.5× 345 3.3× 33 865
Bram De Laere Belgium 14 519 0.8× 438 0.8× 339 0.7× 232 0.9× 115 1.1× 35 793
Sara Ravaioli Italy 16 439 0.6× 330 0.6× 351 0.7× 258 1.0× 212 2.0× 54 939
Kevin Beja Canada 16 1.4k 2.0× 1.0k 2.0× 545 1.1× 552 2.2× 157 1.5× 25 1.7k
Bryce Lakely United States 13 378 0.6× 208 0.4× 239 0.5× 295 1.2× 68 0.7× 16 619

Countries citing papers authored by Adam Jendrisak

Since Specialization
Citations

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

Fields of papers citing papers by Adam Jendrisak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Jendrisak

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Jendrisak. A scholar is included among the top collaborators of Adam Jendrisak 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 Adam Jendrisak. Adam Jendrisak 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.
Conteduca, Vincenza, Sheng‐Yu Ku, Jerry Lee, et al.. (2021). Circulating tumor cell heterogeneity in neuroendocrine prostate cancer by single cell copy number analysis. npj Precision Oncology. 5(1). 76–76. 22 indexed citations
2.
Zhang, Bingnan, C. Allison Stewart, Carl M. Gay, et al.. (2021). Abstract 384: Detection of DNA replication blocker SLFN11 in tumor tissue and circulating tumor cells to predict platinum response in small cell lung cancer. Cancer Research. 81(13_Supplement). 384–384. 6 indexed citations
3.
4.
Jendrisak, Adam, Jerry Lee, Ángel Rodríguez, et al.. (2020). Abstract P4-01-03: Computer vision and machine learning allows for the prediction of genomic instability using circulating tumor cell morphology in triple negative breast cancer patients. Cancer Research. 80(4_Supplement). P4–1. 2 indexed citations
5.
Lu, David, Rachel Krupa, Melissa Harvey, et al.. (2020). Development of an immunofluorescent AR-V7 circulating tumor cell assay – A blood-based test for men with metastatic prostate cancer. SHILAP Revista de lepidopterología. 9(1). 13–19. 8 indexed citations
6.
Schonhoft, Joseph D., Jimmy L. Zhao, Adam Jendrisak, et al.. (2020). Morphology-Predicted Large-Scale Transition Number in Circulating Tumor Cells Identifies a Chromosomal Instability Biomarker Associated with Poor Outcome in Castration-Resistant Prostate Cancer. Cancer Research. 80(22). 4892–4903. 32 indexed citations
9.
Vansant, Gordon, Adam Jendrisak, Joseph D. Schonhoft, et al.. (2018). Analysis of circulating tumor cells (CTCs) in patients across multiple metastatic breast cancer (mBCa) cohorts identifies marked inter- and intra-patient heterogeneity in CTC size, shape, and overall morphology.. Journal of Clinical Oncology. 36(15_suppl). 1084–1084. 2 indexed citations
10.
Dittamore, Ryan, Yipeng Wang, Stephanie Daignault‐Newton, et al.. (2018). Phenotypic and genomic characterization of CTCs as a biomarker for prediction of Veliparib therapy benefit in mCRPC.. Journal of Clinical Oncology. 36(15_suppl). 5012–5012. 2 indexed citations
11.
Scher, Howard I., Ryon P. Graf, Nicole A. Schreiber, et al.. (2017). Phenotypic Heterogeneity of Circulating Tumor Cells Informs Clinical Decisions between AR Signaling Inhibitors and Taxanes in Metastatic Prostate Cancer. Cancer Research. 77(20). 5687–5698. 94 indexed citations
12.
Krupa, Rachel, David Lu, Ryon P. Graf, et al.. (2016). Characterization of programmed cell death-1 ligand (PD-L1) expression in circulating tumor cells (CTCs) of lung cancer. Journal of Thoracic Oncology. 11(2). S52–S52. 1 indexed citations
13.
Anantharaman, Archana, Terence W. Friedlander, David Lu, et al.. (2016). Programmed death-ligand 1 (PD-L1) characterization of circulating tumor cells (CTCs) and white blood cells (WBCs) in muscle invasive and metastatic bladder cancer patients.. Journal of Clinical Oncology. 34(2_suppl). 446–446. 3 indexed citations
15.
Anantharaman, Archana, Terence W. Friedlander, David Lu, et al.. (2016). Programmed death-ligand 1 (PD-L1) characterization of circulating tumor cells (CTCs) in muscle invasive and metastatic bladder cancer patients. BMC Cancer. 16(1). 744–744. 90 indexed citations
16.
Scher, Howard I., Ryon P. Graf, Jessica Louw, et al.. (2016). Single CTC characterization to identify phenotypic and genomic heterogeneity as a mechanism of resistance to AR signaling directed therapies (AR Tx) in mCRPC patients.. Journal of Clinical Oncology. 34(2_suppl). 163–163. 2 indexed citations
17.
Anantharaman, Archana, Terence W. Friedlander, David Lu, et al.. (2016). Programmed death-ligand 1 (PD-L1) characterization of circulating tumor cells (CTCs) in muscle invasive and metastatic bladder cancer patients.. Journal of Clinical Oncology. 34(15_suppl). 4527–4527. 9 indexed citations
18.
Beltran, Himisha, Adam Jendrisak, Mark Landers, et al.. (2015). The Initial Detection and Partial Characterization of Circulating Tumor Cells in Neuroendocrine Prostate Cancer. Clinical Cancer Research. 22(6). 1510–1519. 108 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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