Hüseyin Şeker
- Artificial Intelligence top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Oncology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Khaled BenkridCharalambos ChrysostomouMichael OdetayoDobrila Petrov́ićR.N.G. NaguibAhmet T. ErdoganNizamettin AydınAhmed Bouridane
- Topics
- Machine Learning in Bioinformatics (34 papers)Gene expression and cancer classification (18 papers)Bioinformatics and Genomic Networks (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsComputers in Human Behavior
- Partner nations
- United KingdomTürkiyeUnited States
In The Last Decade
Hüseyin Şeker
99 papers receiving 828 citations
Peers
Comparison fields: 5 of 121
- Artificial Intelligence 339
- Molecular Biology 219
- Computer Vision and Pattern Recognition 137
- Oncology 93
- Radiology, Nuclear Medicine and Imaging 78
Countries citing papers authored by Hüseyin Şeker
This map shows the geographic impact of Hüseyin Şeker'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 Hüseyin Şeker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hüseyin Şeker more than expected).
Fields of papers citing papers by Hüseyin Şeker
This network shows the impact of papers produced by Hüseyin Şeker. 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 Hüseyin Şeker. The network helps show where Hüseyin Şeker may publish in the future.
Co-authorship network of co-authors of Hüseyin Şeker
This figure shows the co-authorship network connecting the top 25 collaborators of Hüseyin Şeker. A scholar is included among the top collaborators of Hüseyin Şeker based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hüseyin Şeker. Hüseyin Şeker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 2 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 13 | |
| 8 | 3 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 9 | |
| 12 | 22 | |
| 13 | 10 | |
| 14 | 3 | |
| 15 | 12 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 98 | |
| 19 | 14 | |
| 20 | Statistical and soft feature evaluation indices for prostate cancer prognostic factor assessments | 2 |
About Hüseyin Şeker
Hüseyin Şeker is a scholar working on Artificial Intelligence, Virology and Molecular Biology, having authored 106 papers that have together received 880 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (34 papers), Gene expression and cancer classification (18 papers) and Bioinformatics and Genomic Networks (12 papers). The work is most often cited by research in Hardware and Architecture (74 citations), Artificial Intelligence (339 citations) and Health Information Management (41 citations). Hüseyin Şeker has collaborated with scholars based in United Kingdom, Türkiye and United States. Frequent co-authors include Khaled Benkrid, Charalambos Chrysostomou, Michael Odetayo, Dobrila Petrov́ić, R.N.G. Naguib, Ahmet T. Erdogan, Nizamettin Aydın, Ahmed Bouridane, C. J. Carmona and María José del Jesús. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Computers in Human Behavior.
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.