Abinit Saha

549 citations
19 papers · 396 · h-index 9

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research

Papers in

    • COVID-19 Clinical Research Studies 5
    • SARS-CoV-2 and COVID-19 Research 4
    • Viral Infections and Outbreaks Research 2
    • Circular RNAs in diseases 2

Abinit Saha

19 papers receiving 393 citations

Peers

Abinit Saha
Comparison fields: 5 of 75
  • Infectious Diseases 198
  • Cancer Research 40
  • Neurology 37
  • Molecular Biology 162
  • Computational Theory and Mathematics 31
Replace Vipul K. Singh with:
Vipul K. Singh United States
Xinghua Li China
Shweta Kumari India
Brigitte M. Krenn Austria
Emiliano Cappello Italy
Hossein Keyvani Iran
Xiaoju Liu China
Mateq Ali Alreshidi Saudi Arabia
Lizdany Flórez‐Álvarez Colombia
Emily Mantlo United States
Abinit Saha relative to Vipul K. Singh United States Vipul K. Singh's profile →
Citations per field
00.5×6.2×
Vipul K. Singh · 1×
Citations per year

Countries citing papers authored by Abinit Saha

Since Specialization
Citations

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

Fields of papers citing papers by Abinit Saha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Abinit Saha, 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 Abinit Saha Line = papers co-authored together Abinit Saha links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2020114
2 202082
3 201743
4 202141
5 202133
6 202215
7 201412
8 202110
9 20189
10 20237
11 20147
12 20237
13 20224
14 20253
15 20223
16 20252
17 20212
18 20231
19 20221

About Abinit Saha

Abinit Saha is a scholar working on Infectious Diseases, Molecular Biology, Neurology, Ecology and Nutrition and Dietetics, having authored 19 papers that have together received 396 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Circular RNAs in diseases (2 papers), Viral Infections and Outbreaks Research (2 papers), Long-Term Effects of COVID-19 (2 papers), MicroRNA in disease regulation (2 papers), Bacterial Genetics and Biotechnology (2 papers) and Bacteriophages and microbial interactions (2 papers). The work is most often cited by research in Infectious Diseases (198 citations), Cancer Research (40 citations), Neurology (37 citations), Molecular Biology (162 citations) and Computational Theory and Mathematics (31 citations). Abinit Saha has collaborated with scholars based in India, South Korea and Taiwan. Frequent co-authors include Manojit Bhattacharya, Chiranjib Chakraborty, Ashish Ranjan Sharma, Sang‐Soo Lee, Garima Sharma, Rudra P. Saha, Manoj Kumar Singh, Govindasamy Agoramoorthy, Soumyananda Chakraborti and Shreya M. Banerjee. Their work appears in journals such as Molecular Therapy — Nucleic Acids, Archives of Medical Research, Reviews in Medical Virology, BioMetals and Current Opinion in Pharmacology.

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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