Abbas Khan

2.4k citations
70 papers · 1.7k · 1 hit paper · h-index 23

Impact in

Papers in

    • vaccines and immunoinformatics approaches 20
    • RNA and protein synthesis mechanisms 7
    • Protein Structure and Dynamics 5
    • SARS-CoV-2 and COVID-19 Research 11

Abbas Khan

65 papers receiving 1.7k citations

Abbas Khan's Hit Papers

Higher infectivity of the SARS‐CoV‐2 new variants is associated with K417N/T, E484K, and N501Y mutants: An insight from structural data 2021 · 267 citations
2670+1+3Years since publication50100150200250

Peers

Abbas Khan
Comparison fields: 5 of 117
  • Infectious Diseases 734
  • Computational Theory and Mathematics 348
  • Molecular Biology 1.0k
  • Immunology 259
  • Biotechnology 101
Replace Abbas Khan with:
Abbas Khan China
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Abbas Khan relative to Abbas Khan China Abbas Khan's profile →
Citations per field
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Abbas Khan · 1×
Citations per year

Countries citing papers authored by Abbas Khan

Since Specialization
Citations

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

Fields of papers citing papers by Abbas Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Higher infectivity of the SARS‐CoV‐2 new variants is associated with K417N/T, E484K, and N501Y mutants: An insight from structural data
Hit paper breakdown →
2021267
2 2019119
3 202086
4 201985
5 202083
6 202177
7 201874
8 201963
9 202160
10 202155
11 201951
12 202041
13 202136
14 202034
15 202034
16 201934
17 202131
18
Report: prevalence and resistance pattern of Pseudomonas aeruginosa against various antibiotics.
200830
19 202029
20 201828

About Abbas Khan

Abbas Khan is a scholar working on Molecular Biology, Infectious Diseases, Computational Theory and Mathematics, Ecology and Radiology, Nuclear Medicine and Imaging, having authored 70 papers that have together received 1.7k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (20 papers), Computational Drug Discovery Methods (12 papers), SARS-CoV-2 and COVID-19 Research (11 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), RNA and protein synthesis mechanisms (7 papers), Bacteriophages and microbial interactions (6 papers), Protein Structure and Dynamics (5 papers) and Immunotherapy and Immune Responses (5 papers). The work is most often cited by research in Infectious Diseases (734 citations), Computational Theory and Mathematics (348 citations), Molecular Biology (1.0k citations), Immunology (259 citations) and Biotechnology (101 citations). Abbas Khan has collaborated with scholars based in Pakistan, China and Saudi Arabia. Frequent co-authors include Dong‐Qing Wei, Syed Shujait Ali, Muhammad Suleman, Anwar Mohammad, Taimoor Ashraf Khan, Shoaib Saleem, Mazhar Khan, Shahzeb Khan, Muhammad Junaid and Aman Chandra Kaushik. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Computers in Biology and Medicine, RSC Advances, Scientific Reports and International Journal of Biological Macromolecules.

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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