Analyzing Sequence Data with Markov Chain Models in Scientific Experiments
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2021/07/21
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Journal
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Indian UGC (journal)
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Refrences69
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Citations4
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Evgenia Paxinou ORCID (unauthenticated)
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Dimitrios Kalles
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Christos T. Panagiotakopoulos
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Vassilios S. Verykios
Cite
Paxinou, Evgenia, et al. “Analyzing Sequence Data With Markov Chain Models in Scientific Experiments”. SN Computer Science, vol. 2, no. 5, 2021, https://doi.org/10.1007/s42979-021-00768-5.
Paxinou, E., Kalles, D., Panagiotakopoulos, C. T., & Verykios, V. S. (2021). Analyzing Sequence Data with Markov Chain Models in Scientific Experiments. SN Computer Science, 2(5). https://doi.org/10.1007/s42979-021-00768-5
Paxinou, Evgenia, Dimitrios Kalles, Christos T. Panagiotakopoulos, and Vassilios S. Verykios. “Analyzing Sequence Data With Markov Chain Models in Scientific Experiments”. SN Computer Science 2, no. 5 (2021). https://doi.org/10.1007/s42979-021-00768-5.
Paxinou E, Kalles D, Panagiotakopoulos CT, Verykios VS. Analyzing Sequence Data with Markov Chain Models in Scientific Experiments. SN Computer Science. 2021;2(5).
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Implementation and Evaluation of a Three‐Dimensional Virtual Reality Biology Lab versus Conventional Didactic Practices in Lab Experimenting with the Photonic Microscope | Biochemistry and Molecular Biology Education |
| 16 | 2020 |
Peppy: A virtual reality environment for exploring the principles of polypeptide structure | Protein Science |
| 15 | 2020 |
Deep Joint Spatiotemporal Network (DJSTN) for Efficient Facial Expression Recognition | Sensors |
| 63 | 2020 |
| 10.3233/IDT-190137 | Intelligent Decision Technologies |
| 2020 | |
StoolNet for Color Classification of Stool Medical Images | Electronics |
| 29 | 2019 |
Citations
Citations Analysis
The category
Technology: Technology (General): Industrial engineering. Management engineering: Information technology 1
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Through the lens of artificial intelligence: A novel study of spherical video-based virtual reality usage in autism and neurotypical participants and was published in 2023. The most recent citation comes from a 2024 study titled High-frequency stock market order transitions during the US–China trade war 2018: A discrete-time Markov chain analysis. This article reached its peak citation in 2023, with 3 citations. It has been cited in 3 different journals, 33% of which are open access. Among related journals, the Computers & Education: X Reality cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.