Sameena Azmi

446 total citations
11 papers, 369 citations indexed

About

Sameena Azmi is a scholar working on Molecular Biology, Toxicology and Immunology. According to data from OpenAlex, Sameena Azmi has authored 11 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 2 papers in Toxicology and 2 papers in Immunology. Recurrent topics in Sameena Azmi's work include Cell death mechanisms and regulation (5 papers), Bioactive Compounds and Antitumor Agents (2 papers) and Immune Response and Inflammation (2 papers). Sameena Azmi is often cited by papers focused on Cell death mechanisms and regulation (5 papers), Bioactive Compounds and Antitumor Agents (2 papers) and Immune Response and Inflammation (2 papers). Sameena Azmi collaborates with scholars based in United States, India and Malaysia. Sameena Azmi's co-authors include Reshma Taneja, Hong Sun, Richárd Kellermayer, Réka Szigeti, Neeta Singh, Aline Gréchez‐Cassiau, Satchidananda Panda, Michèle Teboul, Deepika Dhawan and John B. Hogenesch and has published in prestigious journals such as Journal of Biological Chemistry, Biochemical and Biophysical Research Communications and Cancer Letters.

In The Last Decade

Sameena Azmi

11 papers receiving 364 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sameena Azmi United States 9 208 84 69 66 57 11 369
Noah Jenkins United States 8 223 1.1× 29 0.3× 66 1.0× 34 0.5× 48 0.8× 8 445
Leonardo Bee Italy 6 225 1.1× 198 2.4× 47 0.7× 163 2.5× 35 0.6× 6 466
Cory U. Lago United States 11 354 1.7× 44 0.5× 112 1.6× 163 2.5× 129 2.3× 12 582
B. Herreros Spain 10 260 1.3× 107 1.3× 38 0.6× 64 1.0× 22 0.4× 19 397
Amandine Verlande United States 9 124 0.6× 108 1.3× 33 0.5× 98 1.5× 24 0.4× 13 253
Alex Legg United Kingdom 4 275 1.3× 15 0.2× 52 0.8× 30 0.5× 48 0.8× 8 415
Pankaj Bhalla United States 11 134 0.6× 18 0.2× 38 0.6× 36 0.5× 23 0.4× 22 350
Ana Quaglino Argentina 9 195 0.9× 49 0.6× 94 1.4× 30 0.5× 56 1.0× 9 364
Jean-Yves Maltèse United States 8 249 1.2× 9 0.1× 47 0.7× 212 3.2× 24 0.4× 14 421
Srujana Cherukuri United States 10 247 1.2× 170 2.0× 56 0.8× 125 1.9× 83 1.5× 12 655

Countries citing papers authored by Sameena Azmi

Since Specialization
Citations

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

Fields of papers citing papers by Sameena Azmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sameena Azmi

This figure shows the co-authorship network connecting the top 25 collaborators of Sameena Azmi. A scholar is included among the top collaborators of Sameena Azmi 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 Sameena Azmi. Sameena Azmi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Azmi, Sameena, et al.. (2014). EFFECTIVE HYGROMYCIN CONCENTRATION FOR SELECTION OF Agrobacterium-MEDIATED TRANSGENIC Arabidopsis thaliana. 43(1). 119–123. 6 indexed citations
2.
Kellermayer, Richárd, et al.. (2006). CYLD mutations underlie Brooke–Spiegler, familial cylindromatosis, and multiple familial trichoepithelioma syndromes. Clinical Genetics. 70(3). 246–249. 59 indexed citations
3.
Azmi, Sameena, et al.. (2004). Sharp-1/DEC2 Inhibits Skeletal Muscle Differentiation through Repression of Myogenic Transcription Factors. Journal of Biological Chemistry. 279(50). 52643–52652. 73 indexed citations
4.
Gréchez‐Cassiau, Aline, Satchidananda Panda, Michèle Teboul, et al.. (2004). The Transcriptional Repressor STRA13 Regulates a Subset of Peripheral Circadian Outputs. Journal of Biological Chemistry. 279(2). 1141–1150. 74 indexed citations
5.
Azmi, Sameena, et al.. (2003). mSharp-1/DEC2, a Basic Helix-Loop-Helix Protein Functions as a Transcriptional Repressor of E Box Activity and Stra13 Expression. Journal of Biological Chemistry. 278(22). 20098–20109. 63 indexed citations
6.
Singh, Neeta, et al.. (2002). Insights into the molecular mechanism of apoptosis induced by TNF-α in mouse epidermal JB6-derived RT-101 cells. Biochemical and Biophysical Research Communications. 295(1). 24–30. 17 indexed citations
7.
Azmi, Sameena & Reshma Taneja. (2002). Embryonic expression of mSharp-1/mDEC2, which encodes a basic helix–loop–helix transcription factor. Mechanisms of Development. 114(1-2). 181–185. 21 indexed citations
8.
Singh, Neeta, et al.. (2001). Differential sensitivity of murine myeloid FDC-P1 cells and apoptosis resistant mutant(s) to anticancer drugs. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 474(1-2). 105–112. 3 indexed citations
10.
Azmi, Sameena, et al.. (1997). Adriamycin induces apoptosis in rat thymocytes. Cancer Letters. 111(1-2). 225–231. 8 indexed citations
11.
Azmi, Sameena, Deepika Dhawan, & Neeta Singh. (1996). Calcium ionophore A 23187 induces apoptotic cell death in rat thymocytes. Cancer Letters. 107(1). 97–103. 18 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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