Bihter Daş
Impact in
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- Sentiment Analysis and Opinion Mining
Papers in
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- Machine Learning in Bioinformatics 11
- Fractal and DNA sequence analysis 8
- RNA and protein synthesis mechanisms 5
- Gene expression and cancer classification 4
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- Topic Modeling 6
- Natural Language Processing Techniques 4
- Sentiment Analysis and Opinion Mining 4
- Co-authors
- Resul Daş (11 shared papers)Suat Toraman (7 shared papers)İbrahim Türkoğlu (6 shared papers)Seval Yılmaz (1 shared paper)Harun Uslu (1 shared paper)
In The Last Decade
Bihter Daş
31 papers receiving 257 citations
Peers
Comparison fields: 5 of 77
- Health Information Management 11
- Artificial Intelligence 75
- Environmental Engineering 27
- Computational Theory and Mathematics 26
- Experimental and Cognitive Psychology 20
Countries citing papers authored by Bihter Daş
This map shows the geographic impact of Bihter Daş'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 Bihter Daş with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bihter Daş more than expected).
Fields of papers citing papers by Bihter Daş
This network shows the impact of papers produced by Bihter Daş. 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 Bihter Daş. The network helps show where Bihter Daş may publish in the future.
Co-authors
The 5 scholars most cited alongside Bihter Daş, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 32 | |
| 2 | 2022 | 30 | |
| 3 | 2017 | 24 | |
| 4 | 2024 | 24 | |
| 5 | 2022 | 19 | |
| 6 | 2021 | 18 | |
| 7 | 2024 | 16 | |
| 8 | 2022 | 15 | |
| 9 | 2022 | 11 | |
| 10 | 2023 | 10 | |
| 11 | 2025 | 7 | |
| 12 | 2024 | 7 | |
| 13 | 2022 | 6 | |
| 14 | 2016 | 6 | |
| 15 | 2020 | 5 | |
| 16 | 2024 | 5 | |
| 17 | 2025 | 4 | |
| 18 | 2020 | 4 | |
| 19 | 2020 | 3 | |
| 20 | 2024 | 3 |
About Bihter Daş
Bihter Daş is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems, Computational Theory and Mathematics and Automotive Engineering, having authored 38 papers that have together received 266 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (11 papers), Fractal and DNA sequence analysis (8 papers), Topic Modeling (6 papers), RNA and protein synthesis mechanisms (5 papers), Gene expression and cancer classification (4 papers), Computational Drug Discovery Methods (4 papers), Natural Language Processing Techniques (4 papers) and Sentiment Analysis and Opinion Mining (4 papers). The work is most often cited by research in Health Information Management (11 citations), Artificial Intelligence (75 citations), Environmental Engineering (27 citations), Computational Theory and Mathematics (26 citations) and Experimental and Cognitive Psychology (20 citations). Bihter Daş has collaborated with scholars based in Türkiye, Spain and Poland. Frequent co-authors include Resul Daş, Suat Toraman, İbrahim Türkoğlu, Seval Yılmaz and Harun Uslu. Their work appears in journals such as Chemometrics and Intelligent Laboratory Systems, Neural Computing and Applications, Heliyon, Engineering Applications of Artificial Intelligence and Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi.
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.