Rayees Rahman
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Melanoma and MAPK Pathways
- Bacterial biofilms and quorum sensing
- Bioinformatics and Genomic Networks
Papers in
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- Bioinformatics and Genomic Networks 5
- Machine Learning in Bioinformatics 2
- Gene expression and cancer classification 2
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- Microbial Natural Products and Biosynthesis 5
- Co-authors
- Avner Schlessinger (11 shared papers)Peter M.U. Ung (3 shared papers)Anna Cichońska (3 shared papers)Balaguru Ravikumar (3 shared papers)Stephen Z. Levine (3 shared papers)Abraham Reichenberg (3 shared papers)Sven Sandin (3 shared papers)Arad Kodesh (3 shared papers)
- Journals
- PLoS Computational Biology (2 papers)Nature Communications (2 papers)Biophysical Journal (1 paper)Nucleic Acids Research (1 paper)European Psychiatry (1 paper)
- Partner nations
- United StatesIsraelSweden
In The Last Decade
Rayees Rahman
16 papers receiving 273 citations
Peers
Comparison fields: 5 of 79
- Computational Theory and Mathematics 60
- Molecular Biology 173
- Cognitive Neuroscience 37
- Molecular Medicine 7
- Endocrinology 7
Countries citing papers authored by Rayees Rahman
This map shows the geographic impact of Rayees Rahman'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 Rayees Rahman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rayees Rahman more than expected).
Fields of papers citing papers by Rayees Rahman
This network shows the impact of papers produced by Rayees Rahman. 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 Rayees Rahman. The network helps show where Rayees Rahman may publish in the future.
Co-authors
The 25 scholars most cited alongside Rayees Rahman, 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 | 2018 | 66 | |
| 2 | 2017 | 37 | |
| 3 | 2020 | 33 | |
| 4 | 2020 | 28 | |
| 5 | 2024 | 27 | |
| 6 | 2018 | 24 | |
| 7 | 2018 | 20 | |
| 8 | 2019 | 14 | |
| 9 | 2023 | 13 | |
| 10 | 2017 | 9 | |
| 11 | 2021 | 9 | |
| 12 | 2021 | 5 | |
| 13 | 2024 | 3 | |
| 14 | 2022 | 1 | |
| 15 | 2019 | 1 | |
| 16 | 2021 | 1 |
About Rayees Rahman
Rayees Rahman is a scholar working on Molecular Biology, Pharmacology, Computational Theory and Mathematics, Cognitive Neuroscience and Clinical Psychology, having authored 16 papers that have together received 291 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Microbial Natural Products and Biosynthesis (5 papers), Bioinformatics and Genomic Networks (5 papers), Autism Spectrum Disorder Research (3 papers), Child Nutrition and Feeding Issues (2 papers), Machine Learning in Bioinformatics (2 papers), Family and Disability Support Research (2 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Computational Theory and Mathematics (60 citations), Molecular Biology (173 citations), Cognitive Neuroscience (37 citations), Molecular Medicine (7 citations) and Endocrinology (7 citations). Rayees Rahman has collaborated with scholars based in United States, Israel and Sweden. Frequent co-authors include Avner Schlessinger, Peter M.U. Ung, Anna Cichońska, Balaguru Ravikumar, Stephen Z. Levine, Abraham Reichenberg, Sven Sandin, Arad Kodesh, Jinyuan Yan and Weigang Qiu. Their work appears in journals such as PLoS Computational Biology, Nature Communications, Biophysical Journal, Nucleic Acids Research and European Psychiatry.
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.