Reena Arora

1.5k total citations
121 papers, 1.2k citations indexed

About

Reena Arora is a scholar working on Genetics, Molecular Biology and Agronomy and Crop Science. According to data from OpenAlex, Reena Arora has authored 121 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Genetics, 31 papers in Molecular Biology and 30 papers in Agronomy and Crop Science. Recurrent topics in Reena Arora's work include Genetic and phenotypic traits in livestock (64 papers), Genetic diversity and population structure (31 papers) and Genetic Mapping and Diversity in Plants and Animals (23 papers). Reena Arora is often cited by papers focused on Genetic and phenotypic traits in livestock (64 papers), Genetic diversity and population structure (31 papers) and Genetic Mapping and Diversity in Plants and Animals (23 papers). Reena Arora collaborates with scholars based in India, New Zealand and Japan. Reena Arora's co-authors include Sabhyata Bhatia, Sonika Ahlawat, Rekha Sharma, M. S. Tantia, Ramesh Kumar Vijh, Mandeep Kaur, R. K. Vijh, Bina Mishra, Somdutta Sen and Bishnu Prasad Mishra and has published in prestigious journals such as PLoS ONE, Cancer Research and Analytical Biochemistry.

In The Last Decade

Reena Arora

107 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
Reena Arora India 18 711 342 211 160 121 121 1.2k
Grégoire Harichaux France 17 256 0.4× 320 0.9× 243 1.2× 45 0.3× 158 1.3× 28 1.1k
Elisabeth Jonas Sweden 20 718 1.0× 379 1.1× 132 0.6× 151 0.9× 269 2.2× 47 1.3k
Christa Kühn Germany 19 803 1.1× 543 1.6× 238 1.1× 333 2.1× 127 1.0× 58 1.4k
Yanghua He China 17 241 0.3× 497 1.5× 189 0.9× 176 1.1× 100 0.8× 43 847
Ronald M. Brunner Germany 21 510 0.7× 538 1.6× 494 2.3× 219 1.4× 168 1.4× 81 1.7k
D.S. Gallagher United States 17 807 1.1× 364 1.1× 76 0.4× 72 0.5× 26 0.2× 36 1.1k
V. C. Farr New Zealand 21 526 0.7× 375 1.1× 1.1k 5.2× 141 0.9× 392 3.2× 29 1.7k
Lingzhao Fang China 23 804 1.1× 469 1.4× 271 1.3× 416 2.6× 99 0.8× 84 1.2k
Artur Gurgul Poland 19 722 1.0× 445 1.3× 94 0.4× 238 1.5× 145 1.2× 119 1.2k
Manishi Mukesh India 23 855 1.2× 546 1.6× 484 2.3× 206 1.3× 352 2.9× 124 1.6k

Countries citing papers authored by Reena Arora

Since Specialization
Citations

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

Fields of papers citing papers by Reena Arora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reena Arora

This figure shows the co-authorship network connecting the top 25 collaborators of Reena Arora. A scholar is included among the top collaborators of Reena Arora 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 Reena Arora. Reena Arora 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.
Vijh, R. K., et al.. (2025). Development and validation of a high-density SNP chip tailored for genomic analysis in Indian backyard chickens. British Poultry Science. 66(6). 758–766.
2.
Ahlawat, Sonika, et al.. (2024). Review on camel genetic diversity: ecological and economic perspectives. Mammalian Genome. 35(4). 621–632. 1 indexed citations
3.
Vijh, Ramesh Kumar, et al.. (2024). Development and validation of the Axiom-MaruPri SNP chip for genetic analyses of domesticated old world camelids. Gene. 921. 148541–148541. 3 indexed citations
4.
Arora, Reena, et al.. (2024). Comparative transcriptome analyses of cardiac tissue reveals differential gene expression profiles in sheep in response to altitudinal adaptation. Small Ruminant Research. 238. 107330–107330. 3 indexed citations
5.
6.
Kumar, Amod, G. R. Gowane, Sonika Ahlawat, et al.. (2024). Genomic insights into high-altitude adaptation and evolutionary dynamics of Indian yaks in the Trans-Himalayan region. Conservation Genetics. 26(1). 49–62. 3 indexed citations
7.
Ahlawat, Sonika, et al.. (2024). Unraveling the genetic and physiological potential of donkeys: insights from genomics, proteomics, and metabolomics approaches. Mammalian Genome. 36(1). 10–24. 1 indexed citations
8.
Vijh, Ramesh Kumar, et al.. (2023). Design and validation of high-density SNP array of goats and population stratification of Indian goat breeds. Gene. 885. 147691–147691. 8 indexed citations
9.
Ahlawat, Sonika, Reena Arora, Upasna Sharma, et al.. (2020). Comparative gene expression profiling of milk somatic cells of Sahiwal cattle and Murrah buffaloes. Gene. 764. 145101–145101. 14 indexed citations
10.
Arora, Reena, Anju Sharma, Upasna Sharma, et al.. (2019). Buffalo milk transcriptome: A comparative analysis of early, mid and late lactation. Scientific Reports. 9(1). 5993–5993. 35 indexed citations
11.
Behl, Rahul, S. K. Niranjan, M. S. Tantia, et al.. (2017). Genetic characterization of brown type donkeys of Andhra Pradesh using microsatellite markers. The Indian Journal of Animal Sciences. 87(9). 1 indexed citations
12.
Ahlawat, Sonika, Priyanka Sharma, Rekha Sharma, Reena Arora, & Sachinandan De. (2016). Zinc Finger Domain of the PRDM9 Gene on Chromosome 1 Exhibits High Diversity in Ruminants but Its Paralog PRDM7 Contains Multiple Disruptive Mutations. PLoS ONE. 11(5). e0156159–e0156159. 10 indexed citations
13.
Arora, Reena, et al.. (2014). Exploring Deccani sheep ecotypes of Maharashtra: are these autonomous breeds?. Indian Journal of Small Ruminants (The). 20(1). 91–94. 1 indexed citations
14.
Yadav, Vikash Kumar, et al.. (2012). Ramnad White sheep—Phenotypic and genetic characterization. The Indian Journal of Animal Sciences. 82(9). 1082–1086. 9 indexed citations
15.
Arora, Reena, et al.. (2011). Robust regression for determining selection criterion of breeding rams.. Indian Journal of Small Ruminants (The). 17(2). 166–169. 1 indexed citations
16.
Arora, Reena, et al.. (2011). Morphological characterization, production and reproduction status of Munjal -A threatened sheep population of North-West India. The Indian Journal of Animal Sciences. 81(9). 13 indexed citations
17.
Arora, Reena, et al.. (2011). Genetic variation in the 5′UTR of the KRT2.13 gene of sheep. Animal Science Journal. 83(3). 194–198. 5 indexed citations
18.
Sharma, Rekha, Avinash Pandey, A. Maitra, et al.. (2010). Microsatellite based diversity estimation of Changthangi - a high altitude sheep breed of India.. The Indian Journal of Animal Sciences. 80(5). 436–440. 9 indexed citations
19.
Arora, Reena. (2007). Genetic Characterization and Differentiation of Indian Sheep Breeds Using Microsatellite Marker Information. 29(3). 297–306. 10 indexed citations
20.
Vijh, R. K., et al.. (2005). Comparative evaluation of three buffalo populations using microsatellite markers. The Indian Journal of Animal Sciences. 75(3). 3 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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