Nishika Yadav

744 total citations · 1 hit paper
6 papers, 532 citations indexed

About

Nishika Yadav is a scholar working on Molecular Biology, Pharmaceutical Science and Computational Theory and Mathematics. According to data from OpenAlex, Nishika Yadav has authored 6 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Pharmaceutical Science and 2 papers in Computational Theory and Mathematics. Recurrent topics in Nishika Yadav's work include Computational Drug Discovery Methods (2 papers), Advancements in Transdermal Drug Delivery (1 paper) and Essential Oils and Antimicrobial Activity (1 paper). Nishika Yadav is often cited by papers focused on Computational Drug Discovery Methods (2 papers), Advancements in Transdermal Drug Delivery (1 paper) and Essential Oils and Antimicrobial Activity (1 paper). Nishika Yadav collaborates with scholars based in India, United Kingdom and United States. Nishika Yadav's co-authors include Vijay Mishra, Sourav Thakur, Jessica M. Rosenholm, Kuldeep K. Bansal, Kalvatala Sudhakar, Murtaza M. Tambuwala, Pallavi Nayak, Alaa A. A. Aljabali, Manvendra Pratap Singh and Gaurav Kant Saraogi and has published in prestigious journals such as Current Pharmaceutical Design, Expert Opinion on Drug Delivery and Pharmaceutics.

In The Last Decade

Nishika Yadav

6 papers receiving 514 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Solid Lipid Nanoparticles: Emerging Colloidal Nano Drug Delivery Systems

2018 459 citations Vijay Mishra, Kuldeep K. Bansal et al. Pharmaceutics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nishika Yadav India	5	245	200	136	88	79	6	532
Archana Khosa India	5	281 1.1×	200 1.0×	112 0.8×	78 0.9×	62 0.8×	9	516
Satish Reddi India	6	285 1.2×	198 1.0×	105 0.8×	77 0.9×	55 0.7×	8	511
Renuka S. Managuli India	14	330 1.3×	167 0.8×	144 1.1×	80 0.9×	72 0.9×	18	726
Supandeep Singh Hallan Italy	14	347 1.4×	203 1.0×	126 0.9×	113 1.3×	63 0.8×	20	690
Neha Mallick India	9	266 1.1×	184 0.9×	139 1.0×	60 0.7×	58 0.7×	11	602
Pedzisai A. Makoni South Africa	11	202 0.8×	148 0.7×	115 0.8×	64 0.7×	77 1.0×	17	514
Iti Chauhan India	8	363 1.5×	193 1.0×	119 0.9×	87 1.0×	46 0.6×	35	613
Reza Mahjub Iran	16	258 1.1×	255 1.3×	112 0.8×	102 1.2×	111 1.4×	43	708
Srinivas Reddy Jitta India	12	287 1.2×	194 1.0×	110 0.8×	77 0.9×	39 0.5×	17	578
Sebastián Scioli Montoto Argentina	10	260 1.1×	291 1.5×	170 1.3×	94 1.1×	92 1.2×	14	677

Countries citing papers authored by Nishika Yadav

Since Specialization

Citations

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

Fields of papers citing papers by Nishika Yadav

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nishika Yadav

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

All Works

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6 of 6 papers shown

1.

Mishra, Vijay, Pallavi Nayak, Nishika Yadav, et al.. (2020). Orally administered self-emulsifying drug delivery system in disease management: advancement and patents. Expert Opinion on Drug Delivery. 18(3). 315–332. 41 indexed citations

2.

Mishra, Vijay, Nishika Yadav, Gaurav Kant Saraogi, Murtaza M. Tambuwala, & Namita Giri. (2019). Dendrimer Based Nanoarchitectures in Diabetes Management: An Overview. Current Pharmaceutical Design. 25(23). 2569–2583. 19 indexed citations

3.

Suttee, Ashish, Nishika Yadav, Gurpal Singh, et al.. (2019). A Review on Status of Nanotechnology in Pharmaceutical Sciences. International Journal of Drug Delivery Technology. 9(1). 98–103. 8 indexed citations

4.

Mishra, Vijay, Nishika Yadav, Gurpal Singh, et al.. (2019). Biomedical Potential of Graphene oxide based Nanoformulations: An Overview. International Journal of Drug Delivery Technology. 9(1). 109–113. 1 indexed citations

5.

Thakur, Sourav, et al.. (2019). Bilayer Tablet Based Chronotherapeutics in the Management of Nocturnal Asthma: An Overview. Recent Patents on Drug Delivery & Formulation. 13(2). 74–82. 4 indexed citations

6.

Mishra, Vijay, Kuldeep K. Bansal, Nishika Yadav, et al.. (2018). Solid Lipid Nanoparticles: Emerging Colloidal Nano Drug Delivery Systems. Pharmaceutics. 10(4). 191–191. 459 indexed citations breakdown →

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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