Sameh K. Mohamed
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 6
- Machine Learning in Bioinformatics 5
- Protein Structure and Dynamics 2
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- Advanced Graph Neural Networks 5
- Co-authors
- Vít Nováček (11 shared papers)Aayah Nounu (4 shared papers)Pierre-Yves Vandenbussche (3 shared papers)Luca Costabello (3 shared papers)Mariano Provencio (2 shared papers)Mohan Timilsina (2 shared papers)María Torrente (2 shared papers)Pasquale Minervini (2 shared papers)
- Journals
- Journal of Clinical Medicine (2 papers)Information Sciences (1 paper)JCO Clinical Cancer Informatics (1 paper)PLoS Computational Biology (1 paper)Bioinformatics (1 paper)
- Partner nations
- IrelandUnited KingdomCzechia
In The Last Decade
Sameh K. Mohamed
16 papers receiving 376 citations
Peers
Comparison fields: 5 of 59
- Computational Theory and Mathematics 170
- Health Informatics 7
- Computational Mathematics 3
- Artificial Intelligence 135
- Molecular Biology 254
Countries citing papers authored by Sameh K. Mohamed
This map shows the geographic impact of Sameh K. Mohamed'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 Sameh K. Mohamed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sameh K. Mohamed more than expected).
Fields of papers citing papers by Sameh K. Mohamed
This network shows the impact of papers produced by Sameh K. Mohamed. 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 Sameh K. Mohamed. The network helps show where Sameh K. Mohamed may publish in the future.
Co-authors
The 25 scholars most cited alongside Sameh K. Mohamed, 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 | 2019 | 147 | |
| 2 | 2020 | 88 | |
| 3 | 2020 | 37 | |
| 4 | Predicting Polypharmacy Side-effects Using Knowledge Graph Embeddings. | 2020 | 24 |
| 5 | 2020 | 17 | |
| 6 | 2019 | 17 | |
| 7 | 2023 | 11 | |
| 8 | On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. | 2021 | 10 |
| 9 | 2019 | 7 | |
| 10 | Loss Functions in Knowledge Graph Embedding Models. | 2019 | 6 |
| 11 | 2023 | 5 | |
| 12 | 2019 | 4 | |
| 13 | 2018 | 3 | |
| 14 | 2022 | 1 | |
| 15 | Predicting The Effects of Chemical-Protein Interactions On Proteins Using Tensor Factorisation. | 2020 | 1 |
| 16 | 2021 | 1 |
About Sameh K. Mohamed
Sameh K. Mohamed is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging and Cardiology and Cardiovascular Medicine, having authored 16 papers that have together received 379 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (6 papers), Machine Learning in Bioinformatics (5 papers), Computational Drug Discovery Methods (5 papers), Advanced Graph Neural Networks (5 papers), Lung Cancer Diagnosis and Treatment (2 papers), Lung Cancer Treatments and Mutations (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Protein Structure and Dynamics (2 papers). The work is most often cited by research in Computational Theory and Mathematics (170 citations), Health Informatics (7 citations), Computational Mathematics (3 citations), Artificial Intelligence (135 citations) and Molecular Biology (254 citations). Sameh K. Mohamed has collaborated with scholars based in Ireland, United Kingdom and Czechia. Frequent co-authors include Vít Nováček, Aayah Nounu, Pierre-Yves Vandenbussche, Luca Costabello, Mariano Provencio, Mohan Timilsina, María Torrente, Pasquale Minervini, Bartomeu Massutí and David Matallanas. Their work appears in journals such as Journal of Clinical Medicine, Information Sciences, JCO Clinical Cancer Informatics, PLoS Computational Biology and Bioinformatics.
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.