Michalis Zervakis

1.3k total citations · 1 hit paper
46 papers, 777 citations indexed

About

Michalis Zervakis is a scholar working on Molecular Biology, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michalis Zervakis has authored 46 papers receiving a total of 777 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Cognitive Neuroscience and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michalis Zervakis's work include Gene expression and cancer classification (9 papers), Bioinformatics and Genomic Networks (9 papers) and Functional Brain Connectivity Studies (9 papers). Michalis Zervakis is often cited by papers focused on Gene expression and cancer classification (9 papers), Bioinformatics and Genomic Networks (9 papers) and Functional Brain Connectivity Studies (9 papers). Michalis Zervakis collaborates with scholars based in Greece, United States and United Kingdom. Michalis Zervakis's co-authors include Amir A. Amini, Tahsin Kurç, Andreas S. Panayides, Spyretta Golemati, Constantinos S. Pattichis, Nhan Do, Nenad Filipović, Konstantina S. Nikita, Alistair A. Young and David J. Foran and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Cancer Research.

In The Last Decade

Michalis Zervakis

43 papers receiving 749 citations

Hit Papers

AI in Medical Imaging Inf... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michalis Zervakis Greece 13 215 188 123 99 96 46 777
Qiang Zheng China 15 215 1.0× 104 0.6× 74 0.6× 153 1.5× 199 2.1× 59 856
Ioannis Kalatzis Greece 19 356 1.7× 294 1.6× 130 1.1× 108 1.1× 193 2.0× 73 946
Francesca Gallivanone Italy 21 947 4.4× 237 1.3× 207 1.7× 182 1.8× 83 0.9× 51 1.9k
Meihao Wang China 15 570 2.7× 296 1.6× 78 0.6× 36 0.4× 35 0.4× 51 868
Yongsheng Pan China 16 242 1.1× 230 1.2× 70 0.6× 94 0.9× 267 2.8× 80 1.0k
M. Muthu Rama Krishnan India 20 443 2.1× 463 2.5× 138 1.1× 63 0.6× 309 3.2× 26 1.1k
Richard E. Fan United States 22 522 2.4× 217 1.2× 113 0.9× 159 1.6× 142 1.5× 79 1.5k
Lauren Kim United States 14 469 2.2× 347 1.8× 26 0.2× 55 0.6× 207 2.2× 35 1.0k
Dehan Kong Canada 15 118 0.5× 152 0.8× 62 0.5× 127 1.3× 29 0.3× 56 915
Liangliang Liu China 16 176 0.8× 190 1.0× 46 0.4× 37 0.4× 207 2.2× 48 787

Countries citing papers authored by Michalis Zervakis

Since Specialization
Citations

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

Fields of papers citing papers by Michalis Zervakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michalis Zervakis

This figure shows the co-authorship network connecting the top 25 collaborators of Michalis Zervakis. A scholar is included among the top collaborators of Michalis Zervakis 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 Michalis Zervakis. Michalis Zervakis 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.
Antonakakis, Marios, et al.. (2023). EEG Source Analysis with a Convolutional Neural Network and Finite Element Analysis. PubMed. 2023. 1–4. 2 indexed citations
2.
Papanastasiou, Anastasios D., et al.. (2022). Neuro-inspired Image Compression Architectures. 1 indexed citations
3.
Simos, N., Andrea I. Luppi, Antonios Kagialis, et al.. (2022). Chronic Mild Traumatic Brain Injury: Aberrant Static and Dynamic Connectomic Features Identified Through Machine Learning Model Fusion. Neuroinformatics. 21(2). 427–442. 9 indexed citations
4.
Barnes, Charles D., George Livanos, Michalis Zervakis, et al.. (2021). Fluorescent Imaging and Multifusion Segmentation for Enhanced Visualization and Delineation of Glioblastomas Margins. SHILAP Revista de lepidopterología. 2(2). 304–335. 3 indexed citations
5.
Chalkiadakis, Georgios, et al.. (2021). Dual-Branch CNN for the Identification of Recyclable Materials. 1–6. 3 indexed citations
6.
Antonakakis, Marios, Ümit Aydın, Joachim Groß, et al.. (2020). Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models. NeuroImage. 223. 117353–117353. 57 indexed citations
7.
Pezoulas, Vasileios C., Alkinoos Athanasiou, Guido Nolte, et al.. (2018). FCLAB: An EEGLAB module for performing functional connectivity analysis on single-subject EEG data. 4 indexed citations
9.
Antonakakis, Marios, Stavros I. Dimitriadis, Michalis Zervakis, Andrew C. Papanicolaou, & George Zouridakis. (2017). Reconfiguration of dominant coupling modes in mild traumatic brain injury mediated by δ-band activity: A resting state MEG study. Neuroscience. 356. 275–286. 19 indexed citations
10.
Shrestha, Suman, Yi Wang, George Livanos, et al.. (2017). Multiresolution bioinspired cross-polarized imaging and biostatistics of lung cancer tissue samples. 64. 1–6. 1 indexed citations
11.
Koumakis, Lefteris, Alexandros Kanterakis, Michalis Zervakis, et al.. (2016). MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways. PLoS Computational Biology. 12(11). e1005187–e1005187. 18 indexed citations
12.
Tsolis, Konstantinos C., Ιωάννα Παπαθανασίου, Vasiliki Gkretsi, et al.. (2015). Comparative proteomic analysis of hypertrophic chondrocytes in osteoarthritis. Clinical Proteomics. 12(1). 12–12. 52 indexed citations
13.
Sfakianakis, Stelios, et al.. (2014). On the Identification of Circulating Tumor Cells in Breast Cancer. IEEE Journal of Biomedical and Health Informatics. 18(3). 773–782. 15 indexed citations
14.
Garofalakis, Minos, et al.. (2013). Biological interaction networks based on non-parametric estimation. International Journal of Biomedical Engineering and Technology. 13(4). 383–383.
15.
Gypas, Foivos, et al.. (2011). A disease annotation study of gene signatures in a breast cancer microarray dataset. PubMed. 415. 5551–5554. 1 indexed citations
16.
Sfakianakis, Stelios, Michalis Zervakis, Manolis Tsiknakis, et al.. (2010). Decision support based on genomics: integration of data- and knowledge-driven reasoning. International Journal of Biomedical Engineering and Technology. 3(3/4). 287–287. 4 indexed citations
17.
Sakkalis, Vangelis, et al.. (2009). Activity detection and causal interaction analysis among independent EEG components from memory related tasks. PubMed. 16. 2070–2073. 4 indexed citations
18.
Zervakis, Michalis, et al.. (2009). Outcome prediction based on microarray analysis: a critical perspective on methods. BMC Bioinformatics. 10(1). 53–53. 28 indexed citations
19.
Sakkalis, Vangelis, et al.. (2007). Optimal brain network synchrony visualization: Application in an alcoholism paradigm. Conference proceedings. 65. 4285–4288. 14 indexed citations
20.
Sakkalis, Vangelis, et al.. (2006). Time-significant Wavelet Coherence for the Evaluation of Schizophrenic Brain Activity using a Graph theory approach. PubMed. 2006. 4265–4268. 32 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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