El–Nasir Lalani

6.0k total citations · 1 hit paper
119 papers, 5.1k citations indexed

About

El–Nasir Lalani is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, El–Nasir Lalani has authored 119 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 24 papers in Oncology and 20 papers in Pulmonary and Respiratory Medicine. Recurrent topics in El–Nasir Lalani's work include Glycosylation and Glycoproteins Research (20 papers), Prostate Cancer Treatment and Research (18 papers) and Estrogen and related hormone effects (13 papers). El–Nasir Lalani is often cited by papers focused on Glycosylation and Glycoproteins Research (20 papers), Prostate Cancer Treatment and Research (18 papers) and Estrogen and related hormone effects (13 papers). El–Nasir Lalani collaborates with scholars based in United Kingdom, Pakistan and United States. El–Nasir Lalani's co-authors include Paul Abel, Sandra Gendler, Gordon Stamp, Nigel Peat, Trevor Duhig, Joyce Taylor‐Papadimitriou, Joy Burchell, Lucy F. Pemberton, P D Abel and David B. Wilson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Journal of Biological Chemistry.

In The Last Decade

El–Nasir Lalani

117 papers receiving 4.9k citations

Hit Papers

Molecular cloning and expression of human tumor-associate... 1990 2026 2002 2014 1990 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
El–Nasir Lalani United Kingdom 38 2.7k 1.1k 1.1k 848 699 119 5.1k
Kenneth E. Lipson United States 47 3.3k 1.2× 974 0.9× 1.2k 1.2× 530 0.6× 1.1k 1.6× 123 6.2k
Serge Jothy Canada 37 2.1k 0.8× 1.0k 0.9× 1.3k 1.2× 465 0.5× 458 0.7× 80 4.8k
Yasuhiko Nishioka Japan 41 2.7k 1.0× 1.7k 1.5× 2.3k 2.1× 470 0.6× 1.6k 2.3× 239 6.4k
Gray D. Shaw United States 29 4.1k 1.5× 2.2k 2.0× 960 0.9× 1.0k 1.2× 198 0.3× 52 8.0k
Fabien Calvo France 45 3.3k 1.2× 842 0.8× 2.3k 2.1× 534 0.6× 606 0.9× 160 6.7k
Ana M. Rojas Spain 37 2.3k 0.8× 466 0.4× 455 0.4× 526 0.6× 1.3k 1.8× 114 5.2k
Massimo Pignatelli United Kingdom 52 4.7k 1.7× 759 0.7× 2.4k 2.2× 1.5k 1.7× 925 1.3× 164 8.6k
I. J. Fidler United States 43 3.1k 1.1× 1.6k 1.5× 2.6k 2.4× 464 0.5× 1.2k 1.7× 105 7.0k
Toni Antalis United States 40 2.5k 0.9× 838 0.8× 846 0.8× 646 0.8× 341 0.5× 91 5.7k
Kotoku Kurachi United States 48 4.4k 1.6× 623 0.6× 1.1k 1.0× 473 0.6× 840 1.2× 114 8.6k

Countries citing papers authored by El–Nasir Lalani

Since Specialization
Citations

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

Fields of papers citing papers by El–Nasir Lalani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by El–Nasir Lalani. 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 El–Nasir Lalani. The network helps show where El–Nasir Lalani may publish in the future.

Co-authorship network of co-authors of El–Nasir Lalani

This figure shows the co-authorship network connecting the top 25 collaborators of El–Nasir Lalani. A scholar is included among the top collaborators of El–Nasir Lalani 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 El–Nasir Lalani. El–Nasir Lalani 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.
Minhas, Khurram, et al.. (2025). Prognostic implications of MUC1 and XBP1 concordant expression in multiple myeloma: A retrospective study. PLoS ONE. 20(4). e0320934–e0320934.
2.
Dajani, Rana, Laurie Zoloth, Mohammed Ghaly, et al.. (2022). Diversifying stem cell debates: Including Muslim contexts and perspectives. Stem Cell Reports. 17(5). 1019–1022. 4 indexed citations
3.
Chan, Danny, Susan Garfinkel, Iekuni Ichikawa, et al.. (2020). First meeting in Asia of the Asia Pacific Research Integrity network. Accountability in Research. 27(2). 99–106. 3 indexed citations
4.
Minhas, Khurram, et al.. (2019). LMP1 expression in bone marrow trephines of patients with multiple myeloma confers a survival advantage. Leukemia & lymphoma. 60(8). 1991–2001. 4 indexed citations
5.
Mian, Afsar, et al.. (2019). Activation of AKT/mTOR Pathway in Ph+ Acute Lymphoblastic Leukemia (ALL) Leads to Non-Mutational Resistance. Blood. 134(Supplement_1). 2570–2570. 2 indexed citations
7.
Sądej, Rafał, Hanna Romańska, Gouri Baldwin, et al.. (2009). CD151 Regulates Tumorigenesis by Modulating the Communication between Tumor Cells and Endothelium. Molecular Cancer Research. 7(6). 787–798. 73 indexed citations
8.
Sheikh, Soha El, Jan Domin, Paul Abel, Gordon Stamp, & El–Nasir Lalani. (2004). Phosphorylation of Both EGFR and ErbB2 Is a Reliable Predictor of Prostate Cancer Cell Proliferation in Response to EGF. Neoplasia. 6(6). 846–853. 76 indexed citations
9.
Romańska, Hanna, et al.. (2004). TFF2 (trefoil family factor2) inhibits apoptosis in breast and colorectal cancer cell lines. Peptides. 25(5). 855–863. 25 indexed citations
10.
Sheikh, Soha El, et al.. (2003). Topographical expression of class IA and class II Phosphoinositide 3-kinase Enzymes in normal human tissues is consistent with a role in differentiation. 3(4). 2 indexed citations
11.
Shakil, A. Obaid, et al.. (2003). 116 Serum phosphate as a predictor of clinical outcome in acetaminophen-induced acute liver failure. Hepatology. 38. 212–212. 3 indexed citations
12.
Ockrim, Jeremy, et al.. (2003). Transdermal Estradiol Therapy for Advanced Prostate Cancer—Forward to the Past?. The Journal of Urology. 169(5). 1735–1737. 68 indexed citations
13.
Horne, Andrew W., J.O. White, El–Nasir Lalani, et al.. (2002). Analysis of Epitopes on Endometrial Epithelium by Scanning Immunoelectron Microscopy. Biochemical and Biophysical Research Communications. 292(1). 102–108. 24 indexed citations
15.
Mitchell, SE, et al.. (2000). Androgen dependent up-regulation of MUC1 in an in vitro model of prostate cancer. The Journal of Pathology and Bacteriology. 190. 43. 1 indexed citations
16.
Mubashar, Muhammad, et al.. (1999). Increased reversal of drug resistance with low dose combination of modulators in drug resistant cancer cell lines. European Journal of Nuclear Medicine and Molecular Imaging. 26(9). 988. 1 indexed citations
17.
Lalani, El–Nasir, Richard Poulsom, Andrew Stubbs, et al.. (1998). MT1-MMP and MMP-2 mRNA expression in human ovarian tumors: Possible implications for the role of desmoplastic fibroblasts. Human Pathology. 29(2). 155–165. 81 indexed citations
18.
Stubbs, Andrew, El–Nasir Lalani, Gordon Stamp, et al.. (1996). Second messenger up‐regulation of androgen receptor gene transcription is absent in androgen insensitive human prostatic carcinoma cell lines, PC‐3 and DU‐145. FEBS Letters. 383(3). 237–240. 16 indexed citations
19.
Stamp, G. W. H., et al.. (1993). Transforming growth factor-β distribution in basal cell carcinomas: relationship to proliferation index. British Journal of Dermatology. 129(1). 57–64. 30 indexed citations
20.
Taylor‐Papadimitriou, Joyce, El–Nasir Lalani, Joy Burchell, & Sandra Gendler. (1990). Mucin antigens: Molecular structure and potential use in immunotherapy. 34. 144–150. 1 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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