Göksel Mısırlı
- Signal Processing top 5%
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- Scientific Computing and Data Management 7
- Artificial Intelligence top 5%
- Biophysics top 5%
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- Gene Regulatory Network Analysis 29
- Microbial Metabolic Engineering and Bioproduction 24
- Bioinformatics and Genomic Networks 11
- RNA and protein synthesis mechanisms 5
- Genomics and Phylogenetic Studies 5
- Single-cell and spatial transcriptomics 4
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- Bacterial Genetics and Biotechnology 10
- Co-authors
- Zhong FanAnil WipatChris J. MyersJames Alastair McLaughlinJennifer HallinanMatthew PocockZach ZundelJacob Beal
- Journals
- SHILAP Revista de lepidopterología (1 paper)Bioinformatics (3 papers)IEEE Internet of Things Journal (1 paper)
- Partner nations
- United KingdomUnited StatesSaudi Arabia
In The Last Decade
Göksel Mısırlı
38 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 79
- Signal Processing 187
- Information Systems and Management 95
- Artificial Intelligence 410
- Biophysics 57
- Computer Networks and Communications 225
Countries citing papers authored by Göksel Mısırlı
This map shows the geographic impact of Göksel Mısırlı'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 Göksel Mısırlı with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Göksel Mısırlı more than expected).
Fields of papers citing papers by Göksel Mısırlı
This network shows the impact of papers produced by Göksel Mısırlı. 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 Göksel Mısırlı. The network helps show where Göksel Mısırlı may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Göksel Mısırlı, 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 | 2023 | 10 | |
| 2 | 2022 | 0 | |
| 3 | 2021 | 5 | |
| 4 | 2021 | 10 | |
| 5 | 2021 | 4 | |
| 6 | 2020 | 4 | |
| 7 | 2020 | 16 | |
| 8 | 2020 | 6 | |
| 9 | 2020 | 37 | |
| 10 | Anomaly Detection for IoT Time-Series Data: A Surveybreakdown → | 2020 | 460 |
| 11 | 2017 | 5 | |
| 12 | 2016 | 59 | |
| 13 | 2016 | 22 | |
| 14 | 2015 | 22 | |
| 15 | BBF RFC 108: Synthetic Biology Open Language (SBOL) Version 2.0.0 | 2015 | 1 |
| 16 | 2015 | 7 | |
| 17 | 2014 | 5 | |
| 18 | 2014 | 5 | |
| 19 | 2013 | 10 | |
| 20 | 2010 | 6 |
About Göksel Mısırlı
Göksel Mısırlı is a scholar working on Information Systems and Management, Molecular Biology and Genetics, having authored 40 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (29 papers), Microbial Metabolic Engineering and Bioproduction (24 papers), Bioinformatics and Genomic Networks (11 papers), Bacterial Genetics and Biotechnology (10 papers), Scientific Computing and Data Management (7 papers), RNA and protein synthesis mechanisms (5 papers), Genomics and Phylogenetic Studies (5 papers) and Single-cell and spatial transcriptomics (4 papers). The work is most often cited by research in Signal Processing (187 citations), Information Systems and Management (95 citations) and Artificial Intelligence (410 citations). Göksel Mısırlı has collaborated with scholars based in United Kingdom, United States and Saudi Arabia. Frequent co-authors include Zhong Fan, Anil Wipat, Chris J. Myers, James Alastair McLaughlin, Jennifer Hallinan, Matthew Pocock, Zach Zundel, Jacob Beal, Ernst Oberortner and Curtis Madsen. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Internet of Things Journal.
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.