Vikrant Nain

525 total citations
39 papers, 366 citations indexed

About

Vikrant Nain is a scholar working on Molecular Biology, Plant Science and Biotechnology. According to data from OpenAlex, Vikrant Nain has authored 39 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 12 papers in Plant Science and 5 papers in Biotechnology. Recurrent topics in Vikrant Nain's work include CRISPR and Genetic Engineering (7 papers), Insect Resistance and Genetics (6 papers) and RNA and protein synthesis mechanisms (5 papers). Vikrant Nain is often cited by papers focused on CRISPR and Genetic Engineering (7 papers), Insect Resistance and Genetics (6 papers) and RNA and protein synthesis mechanisms (5 papers). Vikrant Nain collaborates with scholars based in India, United States and Saudi Arabia. Vikrant Nain's co-authors include Anuradha Bhardwaj, Rekha Puria, Shakti Sahi, Anju Verma, Suman Lakhanpaul, Pankaj Kumar, Pragya Sharma, Polumetla Ananda Kumar, Imteyaz Qamar and N. Singh and has published in prestigious journals such as Analytical Biochemistry, Gene and Biochimica et Biophysica Acta (BBA) - Molecular Cell Research.

In The Last Decade

Vikrant Nain

37 papers receiving 354 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vikrant Nain India 10 252 86 50 47 40 39 366
Chaobao Zhang China 8 401 1.6× 99 1.2× 65 1.3× 41 0.9× 19 0.5× 22 528
Xiaojie Cheng China 14 235 0.9× 98 1.1× 29 0.6× 50 1.1× 40 1.0× 33 491
Karambir Kaur India 9 185 0.7× 74 0.9× 24 0.5× 18 0.4× 11 0.3× 17 286
Srividhya Venkataraman Canada 11 255 1.0× 149 1.7× 24 0.5× 17 0.4× 69 1.7× 27 425
Kim Vriens Belgium 12 369 1.5× 79 0.9× 24 0.5× 56 1.2× 75 1.9× 13 537
Christian S. Kaas Denmark 8 288 1.1× 44 0.5× 65 1.3× 5 0.1× 20 0.5× 13 346
André da Silva Santiago Brazil 14 214 0.8× 86 1.0× 27 0.5× 16 0.3× 22 0.6× 25 387
Jianli Tang China 12 212 0.8× 49 0.6× 43 0.9× 99 2.1× 135 3.4× 30 419
Rong Xiao China 11 151 0.6× 58 0.7× 37 0.7× 28 0.6× 13 0.3× 22 380

Countries citing papers authored by Vikrant Nain

Since Specialization
Citations

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

Fields of papers citing papers by Vikrant Nain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vikrant Nain

This figure shows the co-authorship network connecting the top 25 collaborators of Vikrant Nain. A scholar is included among the top collaborators of Vikrant Nain 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 Vikrant Nain. Vikrant Nain 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.
Bhardwaj, Anuradha, Pradeep Tomar, & Vikrant Nain. (2024). Machine Learning-Driven Prediction of CRISPR-Cas9 Off-Target Effects and Mechanistic Insights. The EuroBiotech Journal. 8(4). 213–229.
2.
Awasthi, Amit K., et al.. (2024). Scaled codon usage similarity index: A comprehensive resource for crop plants. Journal of Genetic Engineering and Biotechnology. 22(4). 100441–100441. 1 indexed citations
3.
Puria, Rekha, et al.. (2024). In silico genome wide identification of long non-coding RNAs differentially expressed during Candida auris host pathogenesis. Archives of Microbiology. 206(6). 253–253. 3 indexed citations
4.
5.
Bhardwaj, Anuradha, Pradeep Tomar, & Vikrant Nain. (2023). Identification and evaluation of machine learning classification algorithm to predict the efficacy of gRNA in CRISPR/Cas9 genome editing system using WEKA. AIP conference proceedings. 2977. 40008–40008. 1 indexed citations
6.
Nain, Vikrant, Gothandapani Sellamuthu, Sushil Satish Chhapekar, et al.. (2022). Rifampicin Increases Expression of Plant Codon-Optimized Bacillus thuringiensis δ-Endotoxin Genes in Escherichia coli. The Protein Journal. 41(2). 327–336. 2 indexed citations
7.
Pal, Shilpa, et al.. (2021). Impact of ureolytic and nonureolytic bacteria on self healing of artificial cracks in biofortified concrete. Advances in Materials and Processing Technologies. 8(sup2). 841–860. 5 indexed citations
8.
Bhardwaj, Anuradha & Vikrant Nain. (2021). TALENs—an indispensable tool in the era of CRISPR: a mini review. Journal of Genetic Engineering and Biotechnology. 19(1). 125–125. 76 indexed citations
9.
Aggarwal, Chetana, et al.. (2021). Comparative response of Spodoptera litura challenged per os with Serratia marcescens strains differing in virulence. Journal of Invertebrate Pathology. 183. 107562–107562. 6 indexed citations
10.
Rawal, Preety, Mohsin Hassan, Manish C. Choudhary, et al.. (2019). Endothelial Cell-Derived TGF-β Promotes Epithelial-Mesenchymal Transition via CD133 in HBx-Infected Hepatoma Cells. Frontiers in Oncology. 9. 308–308. 32 indexed citations
11.
Ahmad, Yasmin, et al.. (2019). A convenient and robust protocol for preparation of ODAP-free Lathyrus sativus protein. Analytical Biochemistry. 591. 113544–113544. 1 indexed citations
12.
Kumar, Pavan, et al.. (2018). Novel insights into TOR signalling in Saccharomyces cerevisiae through Torin2. Gene. 669. 15–27. 10 indexed citations
13.
Sharma, Anamika, Vikrant Nain, Rameshwar Tiwari, Surender Singh, & Lata Nain. (2018). Optimization of fermentation condition for co-production of ethanol and 2,3-butanediol (2,3-BD) from hemicellolosic hydrolysates by Klebsiella oxytoca XF7. Chemical Engineering Communications. 205(3). 402–410. 9 indexed citations
14.
Nain, Vikrant, et al.. (2014). Role of TCA cycle Truncation in Cancer Cell Energetics. Current Trends in Biotechnology and Pharmacy. 8(4). 428–438. 1 indexed citations
15.
Nain, Vikrant, et al.. (2014). Cloning and heterologous expression of cellulose free thermostable xylanase from Bacillus brevis. SpringerPlus. 3(1). 20–20. 20 indexed citations
16.
Sahi, Shakti, et al.. (2014). Modelling of Human Leucyl Aminopeptidases for in silico Off Target Binding Analysis of Potential Plasmodium falciparum Leucine Aminopeptidase (PfA-M17) Specific Inhibitors. Recent Patents on Endocrine Metabolic & Immune Drug Discovery. 8(3). 191–201. 3 indexed citations
17.
Dalal, Monika, et al.. (2011). Targeted Integration of Bacillus thuringiensis -Endotoxin cry1Fa1 in Brinjal (Solanum melongena L.). Current Trends in Biotechnology and Pharmacy. 5(2). 1149–1156. 3 indexed citations
18.
Nain, Vikrant, Shakti Sahi, & Anju Verma. (2010). CPP-ZFN: A potential DNA-targeting anti-malarial drug. Malaria Journal. 9(1). 258–258. 16 indexed citations
19.
Sharma, Pragya, Vikrant Nain, Suman Lakhanpaul, & Pankaj Kumar. (2010). Synergistic activity between Bacillus thuringiensis Cry1Ab and Cry1Ac toxins against maize stem borer (Chilo partellus Swinhoe). Letters in Applied Microbiology. 51(1). no–no. 32 indexed citations
20.
Verma, Anju, et al.. (2008). Tissue specific response of Agrobacterium tumefaciens attachment to Sorghum bicolor (L) Moench. Physiology and Molecular Biology of Plants. 14(4). 307–313. 8 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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