Zafar Nawaz

9.4k total citations · 1 hit paper
113 papers, 7.6k citations indexed

About

Zafar Nawaz is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Zafar Nawaz has authored 113 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Molecular Biology, 56 papers in Genetics and 13 papers in Oncology. Recurrent topics in Zafar Nawaz's work include Estrogen and related hormone effects (38 papers), Ubiquitin and proteasome pathways (22 papers) and Retinoids in leukemia and cellular processes (16 papers). Zafar Nawaz is often cited by papers focused on Estrogen and related hormone effects (38 papers), Ubiquitin and proteasome pathways (22 papers) and Retinoids in leukemia and cellular processes (16 papers). Zafar Nawaz collaborates with scholars based in United States, Qatar and Pakistan. Zafar Nawaz's co-authors include Bert W. O’Malley, David M. Lonard, Carolyn L. Smith, Ming‐Jer Tsai, C. Smith, Sophia Y. Tsai, Salman M. Hyder, George M. Stancel, Donald P. McDonnell and Sheikh Riazuddin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Zafar Nawaz

111 papers receiving 7.4k citations

Hit Papers

Coactivator and Corepress... 1997 2026 2006 2016 1997 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
Zafar Nawaz United States 47 4.8k 3.9k 1.3k 732 606 113 7.6k
Sergio A. Oñate United States 29 4.1k 0.8× 3.8k 1.0× 900 0.7× 838 1.1× 823 1.4× 43 6.6k
Steven K. Nordeen United States 40 3.0k 0.6× 2.1k 0.5× 731 0.5× 674 0.9× 756 1.2× 94 5.1k
Robert B. Stein United States 32 4.1k 0.8× 2.3k 0.6× 1.0k 0.8× 356 0.5× 1.1k 1.7× 96 6.7k
Alessandro Weisz Italy 47 4.8k 1.0× 2.1k 0.5× 1.4k 1.1× 2.0k 2.8× 981 1.6× 186 7.7k
Carol A. Lange United States 53 6.5k 1.4× 3.3k 0.8× 3.4k 2.5× 1.7k 2.3× 1.3k 2.1× 140 10.4k
Jun Sun United States 35 2.1k 0.4× 2.5k 0.6× 915 0.7× 355 0.5× 634 1.0× 80 5.1k
Anders Ström Sweden 36 2.4k 0.5× 2.9k 0.8× 1.5k 1.1× 815 1.1× 323 0.5× 68 5.4k
Eric Kalkhoven Netherlands 48 5.8k 1.2× 2.4k 0.6× 1.3k 1.0× 1.1k 1.5× 1.7k 2.7× 102 9.9k
Jean‐Claude Chambard France 34 4.6k 1.0× 972 0.3× 1.2k 0.9× 1.0k 1.4× 874 1.4× 52 7.4k
Joseph L. Napoli United States 59 7.0k 1.5× 2.1k 0.5× 592 0.4× 374 0.5× 995 1.6× 197 10.6k

Countries citing papers authored by Zafar Nawaz

Since Specialization
Citations

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

Fields of papers citing papers by Zafar Nawaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zafar Nawaz

This figure shows the co-authorship network connecting the top 25 collaborators of Zafar Nawaz. A scholar is included among the top collaborators of Zafar Nawaz 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 Zafar Nawaz. Zafar Nawaz 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.
Akiki, Susanna, et al.. (2023). Spontaneous Remission in a Patient with Chronic Myeloid Leukemia: A Case Report. SHILAP Revista de lepidopterología. 16(1). 1073–1079.
2.
Al‐Khawaga, Sara, et al.. (2020). Haploinsufficiency of the FOXA2 associated with a complex clinical phenotype. Molecular Genetics & Genomic Medicine. 8(6). e1086–e1086. 6 indexed citations
3.
Omri, Halima El, Ruba Y. Taha, Adel Elomri, et al.. (2020). Acute Myeloid Leukemia in Qatar (2010–2016): Clinical, Biological, and Prognostic Factors and Treatment Outcomes. Frontiers in Genetics. 11. 553–553. 5 indexed citations
4.
Nawaz, Zafar, et al.. (2018). An uncommon case of chronic myeloid leukemia with variant cytogenetic.. PubMed. 89(3-S). 28–32. 1 indexed citations
5.
Al‐Dewik, Nader, Mariam Al‐Mureikhi, Rehab Ali, et al.. (2015). High diagnostic yield of clinical exome sequencing in Middle Eastern patients with Mendelian disorders. Human Genetics. 134(9). 967–980. 140 indexed citations
6.
Nawaz, Zafar, Sandra E. Ghayad, Mark N. Jabbour, et al.. (2015). p53 Restoration in Induction and Maintenance of Senescence: Differential Effects in Premalignant and Malignant Tumor Cells. Molecular and Cellular Biology. 36(3). 438–451. 19 indexed citations
7.
Buffa, Laura, et al.. (2012). Molecular mechanism of WW‐domain binding protein‐2 coactivation function in estrogen receptor signaling. IUBMB Life. 65(1). 76–84. 21 indexed citations
8.
Catoe, Heath W. & Zafar Nawaz. (2011). E6-AP facilitates efficient transcription at estrogen responsive promoters through recruitment of chromatin modifiers. Steroids. 76(9). 897–902. 19 indexed citations
9.
Ramamoorthy, Sivapriya, et al.. (2010). Isoform-Specific Degradation of PR-B by E6-AP Is Critical for Normal Mammary Gland Development. Molecular Endocrinology. 24(11). 2099–2113. 25 indexed citations
10.
Fu, Wei, Qiuping Ma, Lei Chen, et al.. (2009). MDM2 Acts Downstream of p53 as an E3 Ligase to Promote FOXO Ubiquitination and Degradation. Journal of Biological Chemistry. 284(21). 13987–14000. 159 indexed citations
11.
Moore, S. Jo, H. Dawn Marshall, Leslie Steele, et al.. (2008). The clinical and genetic epidemiology of neuronal ceroid lipofuscinosis in Newfoundland. Clinical Genetics. 74(3). 213–222. 51 indexed citations
12.
Chu, Isabel, Angel Arnaout, Jun Sun, et al.. (2007). Src promotes estrogen-dependent estrogen receptor α proteolysis in human breast cancer. Journal of Clinical Investigation. 117(8). 2205–2215. 72 indexed citations
13.
Wu, Jianbo, Yayun Liang, Zafar Nawaz, & Salman M. Hyder. (2005). Complex agonist-like properties of ICI 182,780 (Faslodex) in human breast cancer cells that predominantly express progesterone receptor-B: implications for treatment resistance.. PubMed. 27(6). 1647–59. 9 indexed citations
14.
Ismail, Ayesha, et al.. (2005). Ubiquitin and control of transcription. Essays in Biochemistry. 41. 69–80. 44 indexed citations
15.
Fu, Guilian, Ayesha Ismail, Sathish Srinivasan, et al.. (2005). Multifunction Steroid Receptor Coactivator, E6-Associated Protein, Is Involved in Development of the Prostate Gland. Molecular Endocrinology. 20(3). 544–559. 66 indexed citations
16.
Ismail, Ayesha & Zafar Nawaz. (2005). Nuclear hormone receptor degradation and gene transcription: An update. IUBMB Life. 57(7). 483–490. 41 indexed citations
17.
Verma, S. R., Ayesha Ismail, Xiuhua Gao, et al.. (2004). The Ubiquitin-Conjugating Enzyme UBCH7 Acts as a Coactivator for Steroid Hormone Receptors. Molecular and Cellular Biology. 24(19). 8716–8726. 74 indexed citations
18.
Nawaz, Zafar, et al.. (1999). Proteasome-dependent degradation of the human estrogen receptor. Proceedings of the National Academy of Sciences. 96(5). 1858–1862. 497 indexed citations
20.

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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