Ishwar S. Parhar

7.3k total citations
194 papers, 5.9k citations indexed

About

Ishwar S. Parhar is a scholar working on Reproductive Medicine, Molecular Biology and Genetics. According to data from OpenAlex, Ishwar S. Parhar has authored 194 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Reproductive Medicine, 56 papers in Molecular Biology and 50 papers in Genetics. Recurrent topics in Ishwar S. Parhar's work include Hypothalamic control of reproductive hormones (100 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (40 papers) and Neuroendocrine regulation and behavior (31 papers). Ishwar S. Parhar is often cited by papers focused on Hypothalamic control of reproductive hormones (100 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (40 papers) and Neuroendocrine regulation and behavior (31 papers). Ishwar S. Parhar collaborates with scholars based in Malaysia, Japan and Australia. Ishwar S. Parhar's co-authors include Satoshi Ogawa, Tomoko Soga, Yasuo Sakuma, Takashi Kitahashi, Fatima M. Nathan, Muhamad Noor Alfarizal Kamarudin, Takayoshi Ubuka, Berta Levavi‐Sivan, Md Shahjahan and Donald W. Pfaff and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and The Journal of Comparative Neurology.

In The Last Decade

Ishwar S. Parhar

191 papers receiving 5.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ishwar S. Parhar Malaysia 43 2.7k 1.9k 1.6k 1.3k 881 194 5.9k
Olivier Kah France 57 2.5k 0.9× 3.9k 2.1× 4.6k 2.8× 1.2k 0.9× 799 0.9× 149 9.5k
Nancy M. Sherwood Canada 51 4.4k 1.6× 1.9k 1.0× 2.6k 1.6× 1.8k 1.4× 1.1k 1.3× 153 8.9k
José Antonio Muñoz‐Cueto Spain 33 1.3k 0.5× 1.3k 0.7× 1.8k 1.1× 369 0.3× 901 1.0× 92 3.7k
Sakaé Kikuyama Japan 41 1.4k 0.5× 902 0.5× 632 0.4× 1.4k 1.0× 1.4k 1.6× 286 6.6k
John P. Chang Canada 39 1.7k 0.6× 795 0.4× 1.8k 1.1× 546 0.4× 705 0.8× 119 4.0k
Kazuyoshi Ukena Japan 53 4.7k 1.7× 2.1k 1.1× 706 0.4× 1.6k 1.3× 2.4k 2.7× 147 8.6k
Riccardo Pierantoni Italy 41 1.9k 0.7× 898 0.5× 763 0.5× 1.2k 0.9× 275 0.3× 161 4.7k
Yasuo Sakuma Japan 40 2.7k 1.0× 1.7k 0.9× 459 0.3× 841 0.6× 1.1k 1.3× 164 5.8k
Isabelle Anglade France 37 774 0.3× 1.6k 0.9× 1.8k 1.1× 393 0.3× 407 0.5× 47 3.6k
Masafumi Amano Japan 31 1.3k 0.5× 873 0.5× 1.5k 0.9× 264 0.2× 784 0.9× 144 3.4k

Countries citing papers authored by Ishwar S. Parhar

Since Specialization
Citations

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

Fields of papers citing papers by Ishwar S. Parhar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ishwar S. Parhar. 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 Ishwar S. Parhar. The network helps show where Ishwar S. Parhar may publish in the future.

Co-authorship network of co-authors of Ishwar S. Parhar

This figure shows the co-authorship network connecting the top 25 collaborators of Ishwar S. Parhar. A scholar is included among the top collaborators of Ishwar S. Parhar 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 Ishwar S. Parhar. Ishwar S. Parhar 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
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Benchoula, Khaled, Christopher J. Serpell, Ahmed Mediani, et al.. (2024). 1H NMR metabolomics insights into comparative diabesity in male and female zebrafish and the antidiabetic activity of DL-limonene. Scientific Reports. 14(1). 3823–3823. 4 indexed citations
3.
Choi, Sy Bing, Satoshi Ogawa, Ishwar S. Parhar, et al.. (2024). Canthin-6-One Inhibits Developmental and Tumour-Associated Angiogenesis in Zebrafish. Pharmaceuticals. 17(1). 108–108. 3 indexed citations
4.
Soga, Tomoko, et al.. (2023). Kisspeptin-10 Mitigates α-Synuclein-Mediated Mitochondrial Apoptosis in SH-SY5Y-Derived Neurons via a Kisspeptin Receptor-Independent Manner. International Journal of Molecular Sciences. 24(7). 6056–6056. 3 indexed citations
5.
Ogawa, Satoshi, et al.. (2023). Integrative Roles of Dopamine Pathway and Calcium Channels Reveal a Link between Schizophrenia and Opioid Use Disorder. International Journal of Molecular Sciences. 24(4). 4088–4088. 2 indexed citations
6.
Parhar, Ishwar S., et al.. (2023). Gender Differences in Cortisol and Cortisol Receptors in Depression: A Narrative Review. International Journal of Molecular Sciences. 24(8). 7129–7129. 21 indexed citations
7.
Soga, Tomoko, et al.. (2023). Social stress-induced serotonin dysfunction activates spexin in male Nile tilapia ( Oreochromis Niloticus ). Proceedings of the National Academy of Sciences. 120(3). e2117547120–e2117547120. 10 indexed citations
8.
Lai, Nicola, et al.. (2023). Teleosts as behaviour test models for social stress. Frontiers in Behavioral Neuroscience. 17. 1205175–1205175. 2 indexed citations
9.
Soga, Tomoko, et al.. (2022). Kisspeptin-10 Rescues Cholinergic Differentiated SHSY-5Y Cells from α-Synuclein-Induced Toxicity In Vitro. International Journal of Molecular Sciences. 23(9). 5193–5193. 6 indexed citations
10.
Benchoula, Khaled, et al.. (2022). Metabolomics based biomarker identification of anti-diabetes and anti-obesity properties of Malaysian herbs. Metabolomics. 18(2). 12–12. 2 indexed citations
11.
Ogawa, Satoshi, et al.. (2022). Receptor-Mediated AKT/PI3K Signalling and Behavioural Alterations in Zebrafish Larvae Reveal Association between Schizophrenia and Opioid Use Disorder. International Journal of Molecular Sciences. 23(9). 4715–4715. 5 indexed citations
12.
Ogawa, Satoshi, et al.. (2021). Multiple gonadotropin‐releasing hormone systems in non‐mammalian vertebrates: Ontogeny, anatomy, and physiology. Journal of Neuroendocrinology. 34(5). e13068–e13068. 17 indexed citations
13.
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Na‐Nakorn, Uthairat, et al.. (2021). A Current Update on the Distribution, Morphological Features, and Genetic Identity of the Southeast Asian Mahseers, Tor Species. Biology. 10(4). 286–286. 16 indexed citations
15.
Ahmad, Bilal, et al.. (2020). Murine in vitro cellular models to better understand adipogenesis and its potential applications. Differentiation. 115. 62–84. 5 indexed citations
16.
Benchoula, Khaled, Ishwar S. Parhar, & Eng Hwa Wong. (2020). The crosstalk of hedgehog, PI3K and Wnt pathways in diabetes. Archives of Biochemistry and Biophysics. 698. 108743–108743. 26 indexed citations
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Ogawa, Satoshi, et al.. (2015). Serotonin Reuptake Inhibitor Citalopram Inhibits GnRH Synthesis and Spermatogenesis in the Male Zebrafish1. Biology of Reproduction. 93(4). 102–102. 33 indexed citations
19.
Soga, Tomoko, et al.. (2015). Early-Life Social Isolation Impairs the Gonadotropin-Inhibitory Hormone Neuronal Activity and Serotonergic System in Male Rats. Frontiers in Endocrinology. 6. 172–172. 19 indexed citations
20.
Ogawa, Satoshi & Ishwar S. Parhar. (2014). Structural and Functional Divergence of Gonadotropin-Inhibitory Hormone from Jawless Fish to Mammals. Frontiers in Endocrinology. 5. 177–177. 57 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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