Kunal Dhiman

825 total citations
18 papers, 556 citations indexed

About

Kunal Dhiman is a scholar working on Physiology, Molecular Biology and Genetics. According to data from OpenAlex, Kunal Dhiman has authored 18 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Physiology, 6 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Kunal Dhiman's work include Alzheimer's disease research and treatments (6 papers), Advances in Cucurbitaceae Research (5 papers) and Dementia and Cognitive Impairment Research (4 papers). Kunal Dhiman is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Advances in Cucurbitaceae Research (5 papers) and Dementia and Cognitive Impairment Research (4 papers). Kunal Dhiman collaborates with scholars based in Australia, Sweden and United Kingdom. Kunal Dhiman's co-authors include N.S. Gill, Veer Bala Gupta, A. Goyal, Atul Gupta, Shailja Sood, Kaj Blennow, Ralph N. Martins, Henrik Zetterberg, Bhim Singh and Qiao‐Xin Li and has published in prestigious journals such as Cellular and Molecular Life Sciences, Neuroscience Letters and Alzheimer s & Dementia.

In The Last Decade

Kunal Dhiman

17 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kunal Dhiman Australia 12 150 146 132 109 103 18 556
Gerusa Duarte Dalmolin Brazil 15 218 1.5× 80 0.5× 297 2.3× 64 0.6× 58 0.6× 17 717
Jitendriya Mishra India 15 102 0.7× 77 0.5× 204 1.5× 56 0.5× 27 0.3× 18 661
Santos Blanco Spain 15 148 1.0× 64 0.4× 171 1.3× 48 0.4× 71 0.7× 27 633
Myeong Sook Cheon Austria 17 156 1.0× 115 0.8× 431 3.3× 148 1.4× 64 0.6× 27 837
Jacqueline Alves Leite Brazil 15 74 0.5× 72 0.5× 280 2.1× 114 1.0× 52 0.5× 27 751
Marı́a G. Campos Mexico 16 157 1.0× 102 0.7× 159 1.2× 82 0.8× 40 0.4× 41 669
Asghar Shabbir Pakistan 11 121 0.8× 28 0.2× 236 1.8× 55 0.5× 33 0.3× 19 599
Ryotaro Saiki Japan 18 100 0.7× 43 0.3× 415 3.1× 43 0.4× 25 0.2× 31 761
Bruno Pinto Brazil 12 95 0.6× 44 0.3× 185 1.4× 90 0.8× 52 0.5× 36 745
Seo Yun Jung South Korea 16 94 0.6× 27 0.2× 232 1.8× 69 0.6× 41 0.4× 44 564

Countries citing papers authored by Kunal Dhiman

Since Specialization
Citations

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

Fields of papers citing papers by Kunal Dhiman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunal Dhiman

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

All Works

18 of 18 papers shown
1.
Chakraborty, Manas, Kunal Dhiman, Perminder S. Sachdev, et al.. (2024). Glutaric acid associates with early detection of cognitive impairment deciphering the association with depression. Alzheimer s & Dementia. 20(S2).
2.
Rajput, Rashi, Nitin Chitranshi, Veer Bala Gupta, et al.. (2022). Neuroserpin, a crucial regulator for axogenesis, synaptic modelling and cell–cell interactions in the pathophysiology of neurological disease. Cellular and Molecular Life Sciences. 79(3). 172–172. 16 indexed citations
4.
Dhiman, Kunal, Victor L. Villemagne, Christopher Fowler, et al.. (2022). Cerebrospinal fluid levels of fatty acid–binding protein 3 are associated with likelihood of amyloidopathy in cognitively healthy individuals. Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring. 14(1). e12377–e12377. 7 indexed citations
5.
Abyadeh, Morteza, Vivek Gupta, Veer Bala Gupta, et al.. (2021). Comparative Analysis of Aducanumab, Zagotenemab and Pioglitazone as Targeted Treatment Strategies for Alzheimer’s Disease. Aging and Disease. 12(8). 1964–1964. 42 indexed citations
6.
Fowler, Christopher, Qiao‐Xin Li, Christopher C. Rowe, et al.. (2020). Decreased cerebrospinal fluid neuronal pentraxin receptor is associated with PET-Aβ load and cerebrospinal fluid Aβ in a pilot study of Alzheimer’s disease. Neuroscience Letters. 731. 135078–135078. 5 indexed citations
7.
Dhiman, Kunal, Victor L. Villemagne, Dhamidhu Eratne, et al.. (2020). Elevated levels of synaptic protein GAP‐43 associate with brain tauopathy, atrophy and cognition in Alzheimer’s disease. Alzheimer s & Dementia. 16(S5). 4 indexed citations
8.
Dhiman, Kunal, Veer Bala Gupta, Victor L. Villemagne, et al.. (2020). Cerebrospinal fluid neurofilament light concentration predicts brain atrophy and cognition in Alzheimer's disease. Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring. 12(1). 66 indexed citations
9.
Dhiman, Kunal, Kaj Blennow, Henrik Zetterberg, Ralph N. Martins, & Veer Bala Gupta. (2019). Cerebrospinal fluid biomarkers for understanding multiple aspects of Alzheimer’s disease pathogenesis. Cellular and Molecular Life Sciences. 76(10). 1833–1863. 77 indexed citations
10.
Eratne, Dhamidhu, Samantha M. Loi, Sarah Farrand, et al.. (2019). A pilot study of the utility of cerebrospinal fluid neurofilament light chain in differentiating neurodegenerative from psychiatric disorders: A ‘C-reactive protein’ for psychiatrists and neurologists?. Australian & New Zealand Journal of Psychiatry. 54(1). 57–67. 35 indexed citations
11.
Dhiman, Kunal, et al.. (2012). Free radical scavenging potential and total phenolic and flavonoid content of Ziziphus mauritiana and Ziziphus nummularia fruit extracts. International Journal of Green Pharmacy. 6(3). 187. 6 indexed citations
12.
Dhiman, Kunal, et al.. (2012). Free radical scavenging potential and total phenolic and flavonoid content of Ziziphus mauritiana and Ziziphus nummularia fruit extracts. International Journal of Green Pharmacy. 6(3). 187–187. 24 indexed citations
13.
Gill, N.S., et al.. (2011). Evaluation of Free Radical Scavenging and Antiulcer Potential of Methanolic Extract of Benincasa hispida Seeds. Research Journal of Medicinal Plant. 5(5). 596–604. 18 indexed citations
14.
Dhiman, Kunal, et al.. (2011). A Review on the Medicinally Important Plants of the Family Cucurbitaceae. 4(1). 16–26. 116 indexed citations
15.
Gill, N.S., et al.. (2010). Evaluation of Antioxidant and Antiulcer Activity of Traditionally Consumed Cucumis melo Seeds. Journal of Pharmacology and Toxicology. 6(1). 82–89. 41 indexed citations
16.
Gill, Naresh Singh, et al.. (2010). Evaluation of Therapeutic Potential of Traditionally Consumed Cucumis melo Seeds. Asian Journal of Plant Sciences. 10(1). 86–91. 43 indexed citations
17.
Gill, N.S., et al.. (2010). Study on Cucumis melo var. utilissimus Seeds for the Therapeutic Potential. Journal of Plant Sciences. 5(3). 248–255. 11 indexed citations
18.
Gill, N.S., et al.. (2010). Evaluation of Free Radical Scavenging, Anti-inflammatory and Analgesic Potential of Benincasa hispida Seed Extract. International Journal of Pharmacology. 6(5). 652–657. 38 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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