Usha Rajamma

1.7k total citations
53 papers, 1.3k citations indexed

About

Usha Rajamma is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Usha Rajamma has authored 53 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 19 papers in Cellular and Molecular Neuroscience and 19 papers in Cognitive Neuroscience. Recurrent topics in Usha Rajamma's work include Autism Spectrum Disorder Research (19 papers), Genetics and Neurodevelopmental Disorders (18 papers) and Mitochondrial Function and Pathology (11 papers). Usha Rajamma is often cited by papers focused on Autism Spectrum Disorder Research (19 papers), Genetics and Neurodevelopmental Disorders (18 papers) and Mitochondrial Function and Pathology (11 papers). Usha Rajamma collaborates with scholars based in India and United States. Usha Rajamma's co-authors include Kochupurackal P. Mohanakumar, Swagata Sinha, Mritunjay Pandey, Reena Haobam, Joy Chakraborty, Saurabh Ghosh, Saravanan S. Karuppagounder, Sindhu K. Madathil, Kanchan Mukhopadhyay and Anindita Chatterjee and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Biochemical Journal.

In The Last Decade

Usha Rajamma

51 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Usha Rajamma India 22 512 387 334 290 190 53 1.3k
Se Jin Jeon South Korea 26 664 1.3× 381 1.0× 447 1.3× 359 1.2× 72 0.4× 86 1.8k
David Dao United States 12 494 1.0× 409 1.1× 148 0.4× 170 0.6× 89 0.5× 27 1.5k
Chengzhong Wang China 16 605 1.2× 198 0.5× 164 0.5× 115 0.4× 42 0.2× 45 1.3k
Sean C. Piantadosi United States 14 360 0.7× 522 1.3× 213 0.6× 83 0.3× 80 0.4× 20 1.5k
Matthew R. Skelton United States 30 388 0.8× 731 1.9× 284 0.9× 84 0.3× 77 0.4× 70 2.1k
Nobutada Tashiro Japan 23 506 1.0× 534 1.4× 251 0.8× 129 0.4× 50 0.3× 63 1.7k
Glenn H. Dillon United States 27 1.0k 2.0× 1.1k 2.8× 238 0.7× 182 0.6× 46 0.2× 60 2.2k
Anete Curte Ferraz Brazil 22 301 0.6× 342 0.9× 119 0.4× 91 0.3× 348 1.8× 32 1.5k
Viviane Labrie United States 25 1.1k 2.1× 765 2.0× 224 0.7× 235 0.8× 576 3.0× 34 2.4k
Mi Kyoung Seo South Korea 22 428 0.8× 434 1.1× 128 0.4× 87 0.3× 67 0.4× 46 1.2k

Countries citing papers authored by Usha Rajamma

Since Specialization
Citations

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

Fields of papers citing papers by Usha Rajamma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Usha Rajamma

This figure shows the co-authorship network connecting the top 25 collaborators of Usha Rajamma. A scholar is included among the top collaborators of Usha Rajamma 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 Usha Rajamma. Usha Rajamma 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.
Nair, K. Saidas, Robert H. George, V. Remya, et al.. (2025). Prevalence Estimates of Neurodevelopmental Disorders (NDD) in a South Indian Population. Annals of Neurosciences. 1556558556–1556558556.
2.
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Rajamma, Usha, et al.. (2025). Computationally designed multi-epitope vaccine construct targeting the SARS-CoV-2 spike protein elicits robust immune responses in silico. Scientific Reports. 15(1). 9562–9562. 6 indexed citations
4.
Rajamma, Usha, et al.. (2022). Efficacy of defensins as neutralizing agents against the deadly SARS-CoV-2. Journal of Biomolecular Structure and Dynamics. 41(7). 2911–2925. 5 indexed citations
5.
Ray, Anirban, et al.. (2018). Genetic variants of the folate metabolic system and mild hyperhomocysteinemia may affect ADHD associated behavioral problems. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 84(Pt A). 1–10. 14 indexed citations
6.
Sinha, Swagata, et al.. (2017). Components of the folate metabolic pathway and ADHD core traits: an exploration in eastern Indian probands. Journal of Human Genetics. 62(7). 687–695. 19 indexed citations
7.
Chandra, Goutam, et al.. (2017). Reinforcing mitochondrial functions in aging brain: An insight into Parkinson's disease therapeutics. Journal of Chemical Neuroanatomy. 95. 29–42. 28 indexed citations
8.
Verma, Poonam, Alpana Singh, Usha Rajamma, et al.. (2016). Attention deficit-hyperactivity disorder suffers from mitochondrial dysfunction. PubMed. 6. 153–158. 49 indexed citations
9.
Sinha, Swagata, Subhrangshu Guhathakurta, Anirban Roychowdhury, et al.. (2016). Genetic variants of MAOB affect serotonin level and specific behavioral attributes to increase autism spectrum disorder (ASD) susceptibility in males. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 71. 123–136. 22 indexed citations
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Guhathakurta, Subhrangshu, Mritunjay Pandey, Merina Varghese, et al.. (2014). SLC6A4 markers modulate platelet 5-HT level and specific behaviors of autism: A study from an Indian population. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 56. 196–206. 28 indexed citations
12.
Rajamma, Usha, et al.. (2014). A Pilot Study on the Contribution of Folate Gene Variants in the Cognitive Function of ADHD Probands. Neurochemical Research. 39(11). 2058–2067. 12 indexed citations
13.
Chakraborty, Joy, R. P. Singh, Debashis Dutta, et al.. (2013). Quercetin Improves Behavioral Deficiencies, Restores Astrocytes and Microglia, and Reduces Serotonin Metabolism in 3‐Nitropropionic Acid‐Induced Rat Model of Huntington's Disease. CNS Neuroscience & Therapeutics. 20(1). 10–19. 110 indexed citations
14.
Karuppagounder, Saravanan S., et al.. (2013). Quercetin up-regulates mitochondrial complex-I activity to protect against programmed cell death in rotenone model of Parkinson’s disease in rats. Neuroscience. 236. 136–148. 182 indexed citations
15.
Rajamma, Usha, et al.. (2011). Glutamate mediated signaling in the pathophysiology of autism spectrum disorders. Pharmacology Biochemistry and Behavior. 100(4). 841–849. 93 indexed citations
16.
Shaw, Jyoti, Arpita Chatterjee, Usha Rajamma, et al.. (2011). Importance of gene variants and co-factors of folate metabolic pathway in the etiology of idiopathic intellectual disability. Nutritional Neuroscience. 14(5). 202–209. 9 indexed citations
17.
Pandey, Mritunjay, Kochupurackal P. Mohanakumar, & Usha Rajamma. (2010). Mitochondrial functional alterations in relation to pathophysiology of Huntington’s disease. Journal of Bioenergetics and Biomembranes. 42(3). 217–226. 23 indexed citations
18.
Sinha, Swagata, et al.. (2009). Family‐based studies indicate association of Engrailed 2 gene with autism in an Indian population. Genes Brain & Behavior. 9(2). 248–255. 35 indexed citations
19.
20.
Jacob, Thomas & Usha Rajamma. (2002). Expression of Cardamom mosaic virus coat protein in Escherichia coli and its assembly into filamentous aggregates. Virus Research. 86(1-2). 133–141. 17 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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