Innovative Research Award
Anastasia Bougea
National and Kapodistrian University of Athens
| Anastasia Bougea |
| Affiliation |
National and Kapodistrian University of Athens |
| Country |
Greece |
| Scopus ID |
55629725400 |
| Documents |
136 |
| Citations |
2352 |
| h-index |
27 |
| Subject Area |
Biological Networks |
| Event |
International Research Awards on Network Science & Graph Analytics |
| ORCID |
0000-0003-3006-8711 |
Anastasia Bougea is a Greek researcher affiliated with the National and Kapodistrian University of Athens whose scholarly work spans neurology, neurodegenerative diseases, clinical neuroscience, digital health, and data-driven approaches to understanding complex biological systems. Her publication record demonstrates sustained contributions to Parkinson’s disease, dementia-related disorders, neuropsychological assessment, and emerging machine-learning methodologies in healthcare research.[1] Through interdisciplinary investigations integrating clinical evidence, neurological biomarkers, and computational analysis, her research aligns with contemporary developments in biological network science and translational medicine.[2]
Abstract
This article summarizes the academic profile of Anastasia Bougea and evaluates her suitability for recognition through the Innovative Research Award. Her body of work reflects a multidisciplinary approach linking neurological disorders, clinical diagnostics, machine learning, mobile health technologies, and molecular mechanisms of neurodegeneration. The scope and continuity of her contributions indicate an active engagement with contemporary biomedical challenges and network-oriented approaches to disease understanding.[3]
Keywords
Biological Networks, Neurodegenerative Diseases, Parkinson’s Disease, Machine Learning, Clinical Neuroscience, Mobile Health, Dementia, Alpha-Synuclein, Biomarkers, Graph Analytics.
Introduction
Research into neurodegenerative diseases increasingly relies on interconnected biological data, computational modeling, and predictive analytics. Anastasia Bougea’s scholarly activities contribute to this evolving landscape through studies addressing disease mechanisms, clinical assessment tools, and technology-assisted healthcare solutions. Her work demonstrates the integration of biomedical knowledge with analytical methods relevant to modern network science applications.[4]
Research Profile
With 136 indexed publications, 2,352 citations, and an h-index of 27, Bougea has established a substantial academic presence. Her research portfolio encompasses Parkinson’s disease, dementia with Lewy bodies, frontotemporal dementia, non-coding RNA therapeutics, and digital health technologies. Her publication activity reflects sustained engagement with peer-reviewed international journals and collaborative research initiatives.[1]
Research Contributions
- Applied machine learning techniques for predicting multiple system atrophy and progressive supranuclear palsy.
- Investigated therapeutic opportunities involving non-coding RNAs in neurodegenerative diseases.
- Reviewed molecular pathways associated with alpha-synuclein and GBA1-related neurological disorders.
- Explored mobile health technologies supporting Parkinson’s disease management.
Publications
- Machine learning-based prediction of multiple system atrophy and progressive supranuclear palsy using clinical and neuropsychological scores (2026).
- Targeting Non-Coding RNAs as a Potential Therapeutic and Delivery Strategy Against Neurodegenerative Diseases (2026).
- Role of Alpha-Synuclein in Frontotemporal Dementia: Narrative Review (2026).
- Underlying Mechanisms of GBA1 in Parkinson’s Disease and Dementia with Lewy Bodies (2025).
- Mobile Health Technologies for the Management of Parkinson’s Disease (2025).
Research Impact
The impact of Bougea’s research is reflected through citation activity, interdisciplinary relevance, and practical implications for neurological healthcare. Her studies support improved understanding of disease progression, digital monitoring technologies, and predictive clinical tools. These contributions help bridge translational research with patient-centered applications and data-driven decision-making frameworks.[5]
Award Suitability
Anastasia Bougea demonstrates characteristics commonly associated with innovative research recognition, including interdisciplinary scholarship, measurable scientific impact, and continued publication productivity. Her integration of machine learning, molecular neuroscience, and mobile health technologies contributes to emerging approaches within biological networks and graph-informed biomedical analysis. These achievements provide a strong basis for consideration within the International Research Awards on Network Science & Graph Analytics.[6]
Conclusion
Bougea’s academic record reflects sustained contributions to neuroscience and neurodegenerative disease research. Her work combines clinical relevance with analytical innovation, supporting advancements in predictive medicine and network-based biomedical understanding. The breadth of her scholarly output and demonstrated impact support recognition within an international research award framework.
External Links
References
- Elsevier. (n.d.). Scopus author details: Anastasia Bougea, Author ID 55629725400. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=55629725400
- Bougea, A. (2026). Machine learning-based prediction of multiple system atrophy and progressive supranuclear palsy using clinical and neuropsychological scores.
DOI: https://doi.org/10.1016/j.bnd.2026.02.002
- Bougea, A. (2026). Targeting Non-Coding RNAs as a Potential Therapeutic and Delivery Strategy Against Neurodegenerative Diseases.
DOI: https://doi.org/10.3390/ijms27073260
- Bougea, A. (2026). Role of Alpha-Synuclein in Frontotemporal Dementia: Narrative Review.
DOI: https://doi.org/10.3390/cells15050470
- Bougea, A. (2025). Underlying Mechanisms of GBA1 in Parkinson’s Disease and Dementia with Lewy Bodies.
DOI: https://doi.org/10.3390/genes16121496
- Bougea, A. (2025). Mobile Health Technologies for the Management of Parkinson’s Disease.
DOI: https://doi.org/10.1080/14737175.2025.2580468