N.A. Shankaracharya

536 citations
13 papers · 206 indexed · h-index 8
Topics
Artificial Intelligence in Healthcare (3 papers)Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers)Enzyme Structure and Function (3 papers)
Partner nations
IndiaUnited States

In The Last Decade

N.A. Shankaracharya

12 papers receiving 193 citations

Peers

N.A. Shankaracharya
Comparison fields: 5 of 73
  • Molecular Biology 80
  • Health Information Management 52
  • Genetics 44
  • Artificial Intelligence 38
  • Biomedical Engineering 21
Replace José Augusto Baranauskas with:
José Augusto Baranauskas Brazil
Aditya Saxena India
Boyd M. Knosp United States
Mert Aydın United States
Advait Balaji United States
Prashanti Manda United States
Azam Yazdani United States
Shinsuke Suemori Japan
Γεώργιος Παπουτσόγλου Greece
Ron Hübler Germany
N.A. Shankaracharya relative to José Augusto Baranauskas Brazil José Augusto Baranauskas's profile →
Citations per field
00.5×7.3×
José Augusto Baranauskas · 1×
Citations per year

Countries citing papers authored by N.A. Shankaracharya

Since Specialization
Citations

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

Fields of papers citing papers by N.A. Shankaracharya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N.A. Shankaracharya. 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 N.A. Shankaracharya. The network helps show where N.A. Shankaracharya may publish in the future.

Co-authorship network of co-authors of N.A. Shankaracharya

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 54
2 1
3 18
4 7
5 6
6 11
7 10
8 9
9
A molecular docking study of anticancer drug paclitaxel and its analogues.
7
10 22
11
Structure Modeling of VRK1 Protein and ITS Molecular Docking Study With Ribavirin Analogs
3
12 54
13 4

About N.A. Shankaracharya

N.A. Shankaracharya is a scholar working on Health Information Management, Applied Microbiology and Biotechnology and Molecular Medicine, having authored 13 papers that have together received 206 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers) and Enzyme Structure and Function (3 papers). The work is most often cited by research in Health Information Management (52 citations), Health Informatics (4 citations) and Genetics (44 citations). N.A. Shankaracharya has collaborated with scholars based in India and United States. Frequent co-authors include Ambarish S. Vidyarthi, Subir Samanta, Devang Odedra, Dinesh Prasad, Abhinav Mathur, Hao Hu, Lynn B. Jorde, Stephen L. Guthery, Gustavo Glusman and Chad D. Huff. Their work appears in journals such as PLoS Genetics, World Journal of Microbiology and Biotechnology and Diabetes Technology & Therapeutics.

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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