Kush Dalal

2.0k total citations
40 papers, 1.2k citations indexed

About

Kush Dalal is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Genetics. According to data from OpenAlex, Kush Dalal has authored 40 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 19 papers in Pulmonary and Respiratory Medicine and 17 papers in Genetics. Recurrent topics in Kush Dalal's work include Prostate Cancer Treatment and Research (19 papers), Estrogen and related hormone effects (10 papers) and Bacterial Genetics and Biotechnology (7 papers). Kush Dalal is often cited by papers focused on Prostate Cancer Treatment and Research (19 papers), Estrogen and related hormone effects (10 papers) and Bacterial Genetics and Biotechnology (7 papers). Kush Dalal collaborates with scholars based in Canada, United States and United Kingdom. Kush Dalal's co-authors include Franck Duong, Artem Cherkasov, Paul S. Rennie, Eric Leblanc, Fuqiang Ban, Stephen G. Sligar, Nada Lallous, Mériem Alami, Barbara Lelj‐Garolla and Huifang Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Kush Dalal

39 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kush Dalal Canada 18 748 384 344 150 142 40 1.2k
Blaine H. M. Mooers United States 23 1.2k 1.6× 212 0.6× 106 0.3× 140 0.9× 237 1.7× 54 1.7k
Hanne Grøn United States 13 737 1.0× 117 0.3× 634 1.8× 181 1.2× 172 1.2× 16 1.2k
Venkatasubramanian Dharmarajan United States 20 1.4k 1.9× 74 0.2× 251 0.7× 57 0.4× 190 1.3× 27 1.8k
Fuzhong F. Zheng United States 7 885 1.2× 109 0.3× 126 0.4× 35 0.2× 173 1.2× 7 1.1k
Leila Su United States 14 514 0.7× 83 0.2× 161 0.5× 36 0.2× 183 1.3× 19 851
Massimiliano Gaetani Sweden 19 637 0.9× 87 0.2× 123 0.4× 156 1.0× 99 0.7× 50 1.3k
Masafumi Kudoh Japan 16 654 0.9× 163 0.4× 185 0.5× 81 0.5× 260 1.8× 28 1.1k
Élisabeth Adjadj France 21 582 0.8× 191 0.5× 134 0.4× 127 0.8× 145 1.0× 39 1.3k
John P. Parisot Australia 13 425 0.6× 93 0.2× 105 0.3× 58 0.4× 193 1.4× 18 802
John Sensintaffar United States 17 2.0k 2.6× 473 1.2× 156 0.5× 132 0.9× 424 3.0× 29 2.8k

Countries citing papers authored by Kush Dalal

Since Specialization
Citations

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

Fields of papers citing papers by Kush Dalal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kush Dalal

This figure shows the co-authorship network connecting the top 25 collaborators of Kush Dalal. A scholar is included among the top collaborators of Kush Dalal 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 Kush Dalal. Kush Dalal 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.
Tam, Kevin J., Liangliang Liu, Michael Hsing, et al.. (2024). Clinically-observed FOXA1 mutations upregulate SEMA3C through transcriptional derepression in prostate cancer. Scientific Reports. 14(1). 7082–7082. 2 indexed citations
2.
Morova, Tunç, Daniel R. McNeill, Nada Lallous, et al.. (2020). Androgen receptor-binding sites are highly mutated in prostate cancer. Nature Communications. 11(1). 832–832. 36 indexed citations
3.
Dalal, Kush, Hélène Morin, Fuqiang Ban, et al.. (2018). Small molecule-induced degradation of the full length and V7 truncated variant forms of human androgen receptor. European Journal of Medicinal Chemistry. 157. 1164–1173. 14 indexed citations
4.
Singh, Kriti, Nada Lallous, Kush Dalal, et al.. (2018). Benzothiophenone Derivatives Targeting Mutant Forms of Estrogen Receptor-α in Hormone-Resistant Breast Cancers. International Journal of Molecular Sciences. 19(2). 579–579. 10 indexed citations
5.
Dalal, Kush, Meixia Che, Aishwariya Sharma, et al.. (2017). Bypassing Drug Resistance Mechanisms of Prostate Cancer with Small Molecules that Target Androgen Receptor–Chromatin Interactions. Molecular Cancer Therapeutics. 16(10). 2281–2291. 27 indexed citations
6.
7.
Borgmann, Hendrik, et al.. (2017). Targeting enzalutamide-resistant prostate cancer using the novel androgen receptor inhibitor ODM-201. European Urology Supplements. 16(3). e1290–e1290. 1 indexed citations
8.
Tam, Kevin J., Kush Dalal, Michael Hsing, et al.. (2016). Androgen receptor transcriptionally regulates semaphorin 3C in a GATA2-dependent manner. Oncotarget. 8(6). 9617–9633. 15 indexed citations
9.
Dalal, Kush, et al.. (2016). Design and Selection of IFI16-PAAD Mutants with Improved dsDNA Destabilization Properties. Journal of Proteomics & Bioinformatics. 9(11).
10.
Borgmann, Hendrik, Kush Dalal, Eliana Beraldi, et al.. (2016). 40 Efficacy of prostate cancer compound with novel mechanism of action targeting the DNA binding domain of the androgen receptor. European Urology Supplements. 15(3). e40–e40. 1 indexed citations
11.
Dalal, Kush, et al.. (2016). Drug-Discovery Pipeline for Novel Inhibitors of the Androgen Receptor. Methods in molecular biology. 1443. 31–54. 5 indexed citations
12.
Bao, Huan, Kush Dalal, Eric N. Cytrynbaum, & Franck Duong. (2015). Sequential Action of MalE and Maltose Allows Coupling ATP Hydrolysis to Translocation in the MalFGK2 Transporter. Journal of Biological Chemistry. 290(42). 25452–25460. 15 indexed citations
13.
Bao, Huan, et al.. (2013). The maltose ABC transporter: Action of membrane lipids on the transporter stability, coupling and ATPase activity. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1828(8). 1723–1730. 31 indexed citations
14.
Fonseca, Bruno D., Graham H. Diering, Michael Bidinosti, et al.. (2012). Structure-Activity Analysis of Niclosamide Reveals Potential Role for Cytoplasmic pH in Control of Mammalian Target of Rapamycin Complex 1 (mTORC1) Signaling. Journal of Biological Chemistry. 287(21). 17530–17545. 131 indexed citations
15.
Dalal, Kush & Franck Duong. (2011). The SecY complex: conducting the orchestra of protein translocation. Trends in Cell Biology. 21(9). 506–514. 19 indexed citations
16.
Dalal, Kush & Franck Duong. (2010). Reconstitution of the SecY Translocon in Nanodiscs. Methods in molecular biology. 619. 145–156. 25 indexed citations
17.
Dalal, Kush, Huan Bao, & Franck Duong. (2010). Modulation of the SecY channel permeability by pore mutations and trivalent cations. Channels. 4(2). 83–86. 4 indexed citations
18.
Dalal, Kush, et al.. (2008). RPA nucleic acid-binding properties of IFI16-HIN200. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1784(7-8). 1087–1097. 46 indexed citations
19.
Alami, Mériem, Kush Dalal, Barbara Lelj‐Garolla, Stephen G. Sligar, & Franck Duong. (2007). Nanodiscs unravel the interaction between the SecYEG channel and its cytosolic partner SecA. The EMBO Journal. 26(8). 1995–2004. 123 indexed citations
20.
Shen, Weiping, et al.. (2005). Target selection of soluble protein complexes for structural proteomics studies.. Proteome Science. 3(1). 3–3. 7 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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