Desh Ranjan

38 papers receiving 279 citations

Peers

Desh Ranjan
Comparison fields: 5 of 52
  • Structural Biology 94
  • Surfaces, Coatings and Films 33
  • Hardware and Architecture 24
  • Computational Theory and Mathematics 47
  • Artificial Intelligence 88
Replace Amos Waterland with:
Amos Waterland United States
Chunshu Wu United States
Wei-Cheng Hsu Taiwan
Poonam Jindal India
Lucian Prodan Romania
Marine Minier France
Matthew J. Holliman United States
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Iman Haghighi United States
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Citations per field
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Amos Waterland · 1×
Citations per year

Countries citing papers authored by Desh Ranjan

Since Specialization
Citations

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

Fields of papers citing papers by Desh Ranjan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Desh Ranjan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Desh Ranjan Line = papers co-authored together Desh Ranjan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201441
2 201429
3 201125
4 201217
5 201617
6 199914
7 201413
8 201011
9 201211
10 201111
11 201410
12 201510
13 20159
14 20118
15 20138
16 20007
17 20146
18 20134
19 20193
20 20223

About Desh Ranjan

Desh Ranjan is a scholar working on Molecular Biology, Computer Networks and Communications, Artificial Intelligence, Structural Biology and Hardware and Architecture, having authored 41 papers that have together received 285 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (9 papers), RNA and protein synthesis mechanisms (8 papers), Algorithms and Data Compression (8 papers), Advanced Electron Microscopy Techniques and Applications (7 papers), Parallel Computing and Optimization Techniques (6 papers), Advanced Data Storage Technologies (6 papers), Enzyme Structure and Function (6 papers) and Particle Accelerators and Free-Electron Lasers (4 papers). The work is most often cited by research in Structural Biology (94 citations), Surfaces, Coatings and Films (33 citations), Hardware and Architecture (24 citations), Computational Theory and Mathematics (47 citations) and Artificial Intelligence (88 citations). Desh Ranjan has collaborated with scholars based in United States and Ghana. Frequent co-authors include Mohammad Zubair, Jing He, Kamal Al Nasr, Abhishek Biswas, Enrico Pontelli, Gopal Gupta, Lin Chen, Balša Terzić, Dong Si and John E. Savage. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Journal of Bioinformatics and Computational Biology, Physical Review Special Topics - Accelerators and Beams, BMC Bioinformatics and Algorithmica.

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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