Salman Sadullah Usmani
- Microbiology top 1%
- Antimicrobial Peptides and Activities 6
- Molecular Biology top 5%
- vaccines and immunoinformatics approaches 14
- Biochemical and Structural Characterization 4
- Machine Learning in Bioinformatics 3
- Chemical Synthesis and Analysis 2
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- Computational Drug Discovery Methods 3
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- Immunotherapy and Immune Responses 4
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- Monoclonal and Polyclonal Antibodies Research 4
- Co-authors
- Gajendra P. S. RaghavaSandeep SinghAnkur GautamSherry BhallaPiyush AgrawalMeenu SharmaGandharva NagpalSandeep Kumar Dhanda
- Partner nations
- IndiaUnited StatesEgypt
In The Last Decade
Salman Sadullah Usmani
24 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Microbiology 432
- Molecular Biology 1.4k
- Computational Theory and Mathematics 159
- Immunology 209
- Radiology, Nuclear Medicine and Imaging 202
Countries citing papers authored by Salman Sadullah Usmani
This map shows the geographic impact of Salman Sadullah Usmani'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 Salman Sadullah Usmani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Salman Sadullah Usmani more than expected).
Fields of papers citing papers by Salman Sadullah Usmani
This network shows the impact of papers produced by Salman Sadullah Usmani. 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 Salman Sadullah Usmani. The network helps show where Salman Sadullah Usmani may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Salman Sadullah Usmani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 4 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 31 | |
| 4 | 2023 | 4 | |
| 5 | 2022 | 47 | |
| 6 | 2021 | 11 | |
| 7 | 2020 | 5 | |
| 8 | 2019 | 55 | |
| 9 | 2018 | 56 | |
| 10 | 2018 | 48 | |
| 11 | 2018 | 38 | |
| 12 | 2018 | 56 | |
| 13 | 2018 | 57 | |
| 14 | 2017 | 221 | |
| 15 | 2017 | 30 | |
| 16 | THPdb: Database of FDA-approved peptide and protein therapeuticsbreakdown → | 2017 | 365 |
| 17 | 2016 | 37 | |
| 18 | 2015 | 169 | |
| 19 | 2015 | 259 | |
| 20 | 2015 | 25 |
About Salman Sadullah Usmani
Salman Sadullah Usmani is a scholar working on Microbiology, Molecular Biology, Developmental Neuroscience, Immunology and Molecular Medicine, having authored 24 papers that have together received 1.7k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (14 papers), Antimicrobial Peptides and Activities (6 papers), Biochemical and Structural Characterization (4 papers), Immunotherapy and Immune Responses (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Computational Drug Discovery Methods (3 papers), Machine Learning in Bioinformatics (3 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Microbiology (432 citations), Molecular Biology (1.4k citations), Computational Theory and Mathematics (159 citations), Immunology (209 citations) and Radiology, Nuclear Medicine and Imaging (202 citations). Salman Sadullah Usmani has collaborated with scholars based in India, United States and Egypt. Frequent co-authors include Gajendra P. S. Raghava, Sandeep Singh, Ankur Gautam, Sherry Bhalla, Piyush Agrawal, Meenu Sharma, Gandharva Nagpal, Sandeep Kumar Dhanda, Kumardeep Chaudhary and Rajesh Kumar. Their work appears in journals such as Scientific Reports, Database, Frontiers in Immunology, Briefings in Bioinformatics and Nucleic Acids Research.
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.