Name: Daniela
Surname: Evangelista
Skill: Researcher
Phone: (Office) +39 0825 299 410
Phone: (Lab) +39 0825 299 410
Fax: +39 0825 299 641
e-mail: daniela.evangelista@isa.cnr.it
CNR People WEB Site: http://www.cnr.it/people/daniela.evangelista
Keywords: Bioinformatics, Clinical Data Mining, Health, Web resource, Machine Learning
Curriculum EN: (click here to view it)
Researcher Activities
I am an interdisciplinary Research Scientist at the National Research Council of Italy (CNR), with expertise in bioinformatics, artificial intelligence, and machine learning applied to biomedical research. My research is centered on the development of computational methods and data integration strategies to address complex biomedical challenges across multiple disease areas. Over the years, I have developed and applied statistical, bioinformatics, and machine learning methods for the analysis of Next Generation Sequencing (NGS) data and contributed to the design of automated decision-support systems for disease diagnosis, prognosis, and patient stratification. These activities have addressed a broad range of clinical conditions, including cancer (e.g., hepatocellular carcinoma, kidney and breast cancers), chronic metabolic disorders, and chromosome 21-related conditions such as Down syndrome. I have also designed and implemented software tools, web platforms, and databases for the management, integration, and analysis of multi-omics, clinical, and experimental data. Currently, at the Institute of Food Sciences in Avellino, my research focuses on bioinformatics and artificial intelligence methodologies for the integration and interpretation of biological and microbiome data. My work spans multiple domains of biomedical research, including oncology and neurodegenerative diseases. By integrating multi-omics, clinical, and microbiome data, I aim to elucidate the molecular mechanisms underlying disease onset and progression and to support the development of data-driven approaches for biomedical research and precision medicine.
Key Publications
- G Felici, KP Tripathi, D Evangelista, MR Guarracino
A mixed integer programming-based global optimization framework for analyzing gene expression data, Journal of Global Optimization 69 (3), 727-744
- D Evangelista, KP Tripathi, MR Guarracino
An Atlas of annotations of Hydra vulgaris transcriptome, BMC bioinformatics 17 (11), 53-59
- D Evangelista, M Avino, P Tripathi, Kumar, MR Guarracino
A Web Resource on Skeletal Muscle Transcriptome of Primates, Springer International Publishing 9874, pp.273-284
- D Evangelista, A Zuccaro, A Lančinskas, J Žilinskas, MR Guarracino
A web-oriented software for the optimization of pooled experiments in NGS for detection of rare mutations, BMC Research Notes 9 (1), 1
- D Evangelista, M Piccirillo, T Ricciardelli, M D’Aiuto, MR Guarracino
A predictive model for surgical planning in breast cancer treatment, 4th International Conference, IWBBIO 2016, Granada, Spain, pp. 454-462
- D Evangelista*, A Zuccaro, MR Guarracino (*Authors contributed equally)
Transcriptator: an automated computational pipeline to annotate assembled reads and identify non coding RNA KP., Tripathi*, Plos One 10 (11), e0140268
- D Evangelista, KP Tripathi, V Scuotto, MR Guarracino
Hvdbase: A web resource on hydra vulgaris transcriptome, International Conference on Bioinformatics and Biomedical Engineering, 355-362
- M Scarpato*, R Esposito*, D Evangelista*, M Aprile, MR Ambrosio, Claudia Angelini, Alfredo Ciccodicola, Valerio Costa (*Authors contributed equally)
AnaLysis of Expression on human chromosome 21, ALE-HSA21: a pilot integrated web resource, Database 2014
- D Evangelista, G Colonna, M Miele, F Cutugno, G Castello, S Desantis, S Costantini
CDMS (Clinical Data Mining Software): a cytokinome data mining system for a predictive medicine of chronic inflammatory diseases, Protein Engineering, Design & Selection 23 (12), 899-902