Jamal Saeh

3.6k total citations · 2 hit papers
35 papers, 2.3k citations indexed

About

Jamal Saeh is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Jamal Saeh has authored 35 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 13 papers in Oncology and 6 papers in Genetics. Recurrent topics in Jamal Saeh's work include Chronic Lymphocytic Leukemia Research (5 papers), Lymphoma Diagnosis and Treatment (5 papers) and CAR-T cell therapy research (4 papers). Jamal Saeh is often cited by papers focused on Chronic Lymphocytic Leukemia Research (5 papers), Lymphoma Diagnosis and Treatment (5 papers) and CAR-T cell therapy research (4 papers). Jamal Saeh collaborates with scholars based in United States, United Kingdom and Australia. Jamal Saeh's co-authors include Paul D. Lyne, Michelle L. Lamb, Lisa Drew, Lecia V. Sequist, A. John Iafrate, Benjamin Solomon, Balázs Halmos, Katherine Crosby, John C. Wain and Cyril H. Benes and has published in prestigious journals such as Journal of the American Chemical Society, The Journal of Chemical Physics and Blood.

In The Last Decade

Jamal Saeh

33 papers receiving 2.2k citations

Hit Papers

Mechanisms of Acquired Crizotinib Resistance in ALK-Rearr... 2006 2026 2012 2019 2012 2006 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jamal Saeh United States 15 1.1k 831 817 328 317 35 2.3k
Amin I. Kassis United States 39 1.5k 1.4× 1.6k 1.9× 537 0.7× 333 1.0× 115 0.4× 161 5.0k
Mindy I. Davis United States 18 2.5k 2.3× 289 0.3× 1.2k 1.4× 214 0.7× 716 2.3× 38 4.6k
Daniella Zheleva United Kingdom 23 1.5k 1.4× 220 0.3× 830 1.0× 100 0.3× 92 0.3× 56 2.2k
J. Breed United Kingdom 34 2.4k 2.2× 197 0.2× 582 0.7× 169 0.5× 179 0.6× 51 3.4k
Roxana E. Iacob United States 24 1.6k 1.5× 581 0.7× 679 0.8× 132 0.4× 100 0.3× 34 2.4k
G. Snell United States 23 1.0k 1.0× 143 0.2× 371 0.5× 157 0.5× 153 0.5× 56 2.8k
Christopher G. Mayne United States 23 1.0k 1.0× 134 0.2× 296 0.4× 111 0.3× 188 0.6× 45 2.1k
Eric Masson United States 32 1.1k 1.0× 315 0.4× 868 1.1× 193 0.6× 38 0.1× 118 4.1k
Thierry Fischmann United States 21 1.5k 1.4× 219 0.3× 486 0.6× 91 0.3× 180 0.6× 37 2.4k
Congxin Liang United States 21 974 0.9× 150 0.2× 437 0.5× 199 0.6× 36 0.1× 29 2.2k

Countries citing papers authored by Jamal Saeh

Since Specialization
Citations

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

Fields of papers citing papers by Jamal Saeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jamal Saeh

This figure shows the co-authorship network connecting the top 25 collaborators of Jamal Saeh. A scholar is included among the top collaborators of Jamal Saeh 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 Jamal Saeh. Jamal Saeh 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.
Chatterjee, Saptarshi, Mathew V. Jones, Yaowu He, et al.. (2025). Aurora B inhibition induces hyper-polyploidy and loss of long-term proliferative potential in RB and p53 defective cells. Cell Death and Disease. 16(1). 7–7. 2 indexed citations
2.
Bonfim‐Melo, Alexis, Yoon Lim, Yaowu He, et al.. (2024). Aurora B inhibitors promote RB hypophosphorylation and senescence independent of p53-dependent CDK2/4 inhibition. Cell Death and Disease. 15(11). 810–810. 4 indexed citations
3.
Desai, Pinkal, Sagar Lonial, Amanda F. Cashen, et al.. (2024). A Phase 1 First-in-Human Study of the MCL-1 Inhibitor AZD5991 in Patients with Relapsed/Refractory Hematologic Malignancies. Clinical Cancer Research. 30(21). 4844–4855. 15 indexed citations
4.
Augustson, Bradley, Hira Mian, Edward A. Stadtmauer, et al.. (2024). A Phase I/II Study of AZD0305, a Novel Antibody-Drug Conjugate (ADC) Targeting GPRC5D, in Patients with Relapsed/Refractory Multiple Myeloma (RRMM). Blood. 144(Supplement 1). 2000.2–2000.2. 1 indexed citations
5.
Ramkumar, Kavya, Azusa Tanimoto, Carminia M. Della Corte, et al.. (2023). Targeting BCL2 Overcomes Resistance and Augments Response to Aurora Kinase B Inhibition by AZD2811 in Small Cell Lung Cancer. Clinical Cancer Research. 29(16). 3237–3249. 14 indexed citations
6.
Hamilton, Erika, Judy S. Wang, Amit M. Oza, et al.. (2023). First-in-human Study of AZD5153, A Small-molecule Inhibitor of Bromodomain Protein 4, in Patients with Relapsed/Refractory Malignant Solid Tumors and Lymphoma. Molecular Cancer Therapeutics. 22(10). 1154–1165. 14 indexed citations
7.
Strati, Paolo, Franck Morschhauser, Alexey V. Danilov, et al.. (2023). P1126: PHASE 1B/2A STUDY OF AZD4573 (CDK9I) AND ACALABRUTINIB IN PATIENTS (PTS) WITH RELAPSED/REFRACTORY DIFFUSE LARGE B-CELL LYMPHOMA (R/R DLBCL). HemaSphere. 7(S3). e47925e9–e47925e9. 1 indexed citations
11.
Yu, Ziyang, Suqin He, Hitisha Patel, et al.. (2017). Selective Androgen Receptor Modulator RAD140 Inhibits the Growth of Androgen/Estrogen Receptor–Positive Breast Cancer Models with a Distinct Mechanism of Action. Clinical Cancer Research. 23(24). 7608–7620. 23 indexed citations
12.
Hennessy, Edward J., Gurmit Grewal, Kate F. Byth, et al.. (2015). Discovery of heterocyclic sulfonamides as sphingosine 1-phosphate receptor 1 (S1P1) antagonists. Bioorganic & Medicinal Chemistry Letters. 25(10). 2041–2045. 2 indexed citations
13.
Varnes, Jeffrey, Thomas W. Gero, Shan Huang, et al.. (2014). Towards the next generation of dual Bcl-2/Bcl-xL inhibitors. Bioorganic & Medicinal Chemistry Letters. 24(14). 3026–3033. 14 indexed citations
14.
Hird, Alexander W., Brian Aquila, M. Block, et al.. (2014). Structure-based design and synthesis of tricyclic IAP (Inhibitors of Apoptosis Proteins) inhibitors. Bioorganic & Medicinal Chemistry Letters. 24(7). 1820–1824. 4 indexed citations
15.
Dowling, James J., Marat Alimzhanov, M. Block, et al.. (2013). Structure and Property Based Design of Pyrazolo[1,5-a]pyrimidine Inhibitors of CK2 Kinase with Activity in Vivo. ACS Medicinal Chemistry Letters. 4(8). 800–805. 41 indexed citations
16.
Wu, Jiaquan, Francoise Powell, Nicholas Larsen, et al.. (2012). Mechanism and In Vitro Pharmacology of TAK1 Inhibition by (5Z)-7-Oxozeaenol. ACS Chemical Biology. 8(3). 643–650. 118 indexed citations
17.
Buglio, Daniela, Sangeetha Palakurthi, Kate F. Byth, et al.. (2012). Essential role of TAK1 in regulating mantle cell lymphoma survival. Blood. 120(2). 347–355. 50 indexed citations
18.
Hennessy, Edward J., Jamal Saeh, Sha Li, et al.. (2011). Discovery of aminopiperidine-based Smac mimetics as IAP antagonists. Bioorganic & Medicinal Chemistry Letters. 22(4). 1690–1694. 17 indexed citations
19.
Saeh, Jamal, Paul D. Lyne, Bryan K. Takasaki, & David A. Cosgrove. (2005). Lead Hopping Using SVM and 3D Pharmacophore Fingerprints. Journal of Chemical Information and Modeling. 45(4). 1122–1133. 41 indexed citations
20.
Saeh, Jamal & John F. Stanton. (1999). Application of an equation-of-motion coupled cluster method including higher-order corrections to potential energy surfaces of radicals. The Journal of Chemical Physics. 111(18). 8275–8285. 58 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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