Charalambos Chrysostomou

1.3k total citations
27 papers, 262 citations indexed

About

Charalambos Chrysostomou is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Charalambos Chrysostomou has authored 27 papers receiving a total of 262 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 5 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Biomedical Engineering. Recurrent topics in Charalambos Chrysostomou's work include Machine Learning in Bioinformatics (12 papers), Fractal and DNA sequence analysis (9 papers) and Medical Imaging Techniques and Applications (4 papers). Charalambos Chrysostomou is often cited by papers focused on Machine Learning in Bioinformatics (12 papers), Fractal and DNA sequence analysis (9 papers) and Medical Imaging Techniques and Applications (4 papers). Charalambos Chrysostomou collaborates with scholars based in United Kingdom, Cyprus and France. Charalambos Chrysostomou's co-authors include Hüseyin Şeker, Nizamettin Aydın, Zacharias M. Nikolaou, Luc Vervisch, Stewart Cant, C. J. Carmona, Wendy Dirks, María José del Jesús, Kirsi O. Lorentz and Yuki Minamoto and has published in prestigious journals such as The Journal of Chemical Physics, Applied Soft Computing and Energies.

In The Last Decade

Charalambos Chrysostomou

26 papers receiving 257 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Charalambos Chrysostomou United Kingdom 10 95 56 33 30 28 27 262
Oskar Wysocki United Kingdom 7 36 0.4× 19 0.3× 11 0.3× 48 1.6× 24 197
Iain Bethune United Kingdom 6 49 0.5× 44 0.8× 5 0.2× 10 0.3× 24 167
Fengye Chen China 11 51 0.5× 33 0.6× 44 1.5× 60 2.1× 16 363
Jiaying Xu China 11 75 0.8× 32 0.6× 7 0.2× 5 0.2× 30 327
Nico Verbeeck United States 8 259 2.7× 43 0.8× 19 0.6× 2 0.1× 15 498
Ruthmara Corzo United States 10 20 0.2× 20 0.4× 32 1.1× 168 6.0× 23 284
Sabia Z. Abidi United States 6 20 0.2× 6 0.1× 8 0.2× 57 1.9× 11 304
Da Xu China 8 105 1.1× 36 0.6× 45 1.5× 31 280
Frédéric Richard France 11 14 0.1× 17 0.3× 66 2.2× 40 1.4× 29 323
Amir Shahmoradi United States 11 49 0.5× 9 0.2× 2 0.1× 7 0.2× 22 276

Countries citing papers authored by Charalambos Chrysostomou

Since Specialization
Citations

This map shows the geographic impact of Charalambos Chrysostomou'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 Charalambos Chrysostomou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charalambos Chrysostomou more than expected).

Fields of papers citing papers by Charalambos Chrysostomou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charalambos Chrysostomou. 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 Charalambos Chrysostomou. The network helps show where Charalambos Chrysostomou may publish in the future.

Co-authorship network of co-authors of Charalambos Chrysostomou

This figure shows the co-authorship network connecting the top 25 collaborators of Charalambos Chrysostomou. A scholar is included among the top collaborators of Charalambos Chrysostomou 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 Charalambos Chrysostomou. Charalambos Chrysostomou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Αγαπίου, Άθως, et al.. (2023). An Application of Machine Learning Algorithms by Synergetic Use of SAR and Optical Data for Monitoring Historic Clusters in Cypriot Cities. Energies. 16(8). 3461–3461. 3 indexed citations
2.
Chrysostomou, Charalambos. (2023). Deep Learning-Assisted Classification of Allergenic Proteins: An Exploration of Amino Acid Indices. 4881–4883. 1 indexed citations
3.
Chrysostomou, Charalambos, et al.. (2022). Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models. The Journal of Chemical Physics. 157(18). 184903–184903. 10 indexed citations
4.
Chrysostomou, Charalambos, et al.. (2021). Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. 1682–1685. 3 indexed citations
5.
Chrysostomou, Charalambos, et al.. (2021). Data Acquisition and Analysis at the X-ray Computed Tomography Beamline of SESAME. 134–139. 2 indexed citations
6.
Chrysostomou, Charalambos. (2021). The Effect of Loss Functions on Denoising and Reconstructing Sinograms Based on Deep Learning Methodologies. 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). 1–4. 1 indexed citations
7.
Lorentz, Kirsi O., et al.. (2020). First permanent molars with accentuated line patterns: Assessment of childhood health in an urban complex of the fifth millennium before the present. Archives of Oral Biology. 123. 104969–104969. 3 indexed citations
8.
Voskarides, Konstantinos, Harsh Dweep, & Charalambos Chrysostomou. (2019). Evidence that DNA repair genes, a family of tumor suppressor genes, are associated with evolution rate and size of genomes. Human Genomics. 13(1). 26–26. 10 indexed citations
9.
Nikolaou, Zacharias M., Charalambos Chrysostomou, Luc Vervisch, & Stewart Cant. (2019). Progress Variable Variance and Filtered Rate Modelling Using Convolutional Neural Networks and Flamelet Methods. Flow Turbulence and Combustion. 103(2). 485–501. 44 indexed citations
10.
Lorentz, Kirsi O., et al.. (2019). Use of dental microstructure to investigate the role of prenatal and early life physiological stress in age at death. Journal of Archaeological Science. 104. 85–96. 29 indexed citations
11.
Vermunt, Lisa, Colin Veal, Charalambos Chrysostomou, et al.. (2018). European Prevention of Alzheimer's Dementia Registry: Recruitment and prescreening approach for a longitudinal cohort and prevention trials. Alzheimer s & Dementia. 14(6). 837–842. 20 indexed citations
12.
Chrysostomou, Charalambos, et al.. (2018). A Reconstruction Method Based on Deep Convolutional Neural Network for SPECT Imaging. 1–4. 4 indexed citations
13.
Elizondo, David, Shang‐Ming Zhou, & Charalambos Chrysostomou. (2016). Light source detection for digital images in noisy scenes: a neural network approach. Neural Computing and Applications. 28(5). 899–909. 4 indexed citations
14.
Chrysostomou, Charalambos & Hüseyin Şeker. (2016). Structural classification of protein sequences based on signal processing and support vector machines. PubMed. 2016. 3088–3091. 4 indexed citations
15.
Chrysostomou, Charalambos & Hüseyin Şeker. (2014). Prediction of protein allergenicity based on signal-processing bioinformatics approach. PubMed. 2014. 808–811. 12 indexed citations
16.
Chrysostomou, Charalambos & Hüseyin Şeker. (2013). Construction of protein distance matrix based on amino acid indices and Discrete Fourier Transform. PubMed. 20. 4066–4069. 2 indexed citations
17.
Chrysostomou, Charalambos & Hüseyin Şeker. (2013). Signal-processing-based bioinformatics approach for the identification of influenza A virus subtypes in Neuraminidase genes. PubMed. 2013. 3066–3069. 3 indexed citations
18.
Carmona, C. J., Charalambos Chrysostomou, Hüseyin Şeker, & María José del Jesús. (2013). Fuzzy rules for describing subgroups from Influenza A virus using a multi-objective evolutionary algorithm. Applied Soft Computing. 13(8). 3439–3448. 20 indexed citations
19.
Chrysostomou, Charalambos, Hüseyin Şeker, & Nizamettin Aydın. (2011). Effects of windowing and zero-padding on Complex Resonant Recognition Model for protein sequence analysis. PubMed. 2011. 4955–8. 10 indexed citations
20.
Chrysostomou, Charalambos, Hüseyin Şeker, Nizamettin Aydın, & Parvez I. Haris. (2010). Complex Resonant Recognition Model in analysing Influenza a virus subtype protein sequences. DMU Open Research Archive (De Montfort University). 1–4. 8 indexed citations

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.

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