Dr. Daniela Evangelista, Consiglio Nazionale delle Ricerche, Italy

Dr. Daniela Evangelista is a Research Scientist at the National Research Council of Italy, Institute of Food Sciences (CNR-ISA). She earned her Ph.D. in Computational Biology from the University of Campania “L. Vanvitelli,” focusing on software systems for interactive analysis of “omics” data, and holds an MSc in Computer Science from the University of Naples “Federico II.” Her career includes roles as a Computer Scientist at ProtoDesign s.r.l. and a Post-Doc Fellow at CNR-ICAR, where she developed software and databases for complex data analysis. Dr. Evangelista is known for her contributions to web-oriented resources for genetic data analysis and diagnostic decision support systems, with numerous publications in journals such as BMC Bioinformatics and PLoS ONE. Her expertise spans programming languages, machine learning, web application development, and NGS technology, reflecting her impact on genomics and personalized medicine.

Suitability for the Best Researcher Award:

Dr. Evangelista’s extensive research output, her leadership in high-impact projects, and her contributions to bioinformatics make her a strong candidate for the Best Researcher Award. Her innovative work in developing software systems for the analysis of omics and clinical data, coupled with her role in advancing the field through significant publications and projects, aligns well with the award’s criteria for excellence in research.

Professional Profile

Google Scholar

Educational Background

Dr. Daniela Evangelista holds a Ph.D. in Computational Biology from the University of Campania “L. Vanvitelli,” where she specialized in developing software systems for interactive analysis of “omics” data. She also earned an MSc in Computer Science from the University of Naples “Federico II,” highlighting her strong foundation in computer science and bioinformatics. Dr. Evangelista’s academic background underscores her expertise in leveraging computational techniques to advance the analysis and interpretation of complex biological data.

Professional Experience

Dr. Daniela Evangelista is currently a Research Scientist at the National Research Council of Italy, Institute of Food Sciences (CNR-ISA). Her previous roles include serving as a Computer Scientist at ProtoDesign s.r.l. and as a Post-Doc Fellow at CNR-ICAR, where she specialized in designing and developing software and databases for analyzing complex data.

Research Contributions

Dr. Evangelista has contributed to the development of web-oriented resources and software tools for analyzing high-throughput genetic data. Her notable work includes a web resource for trisomy of human chromosome 21 and the design of diagnostic decision support systems and automatic classification applications.

Publications and Impact

She has published numerous articles in prestigious journals, such as the Journal of Global Optimization, BMC Bioinformatics, and PLoS ONE. Her research covers gene expression data analysis, transcriptome annotation, and clinical data mining, with practical implications in genomics and personalized medicine.

Skills and Expertise

Dr. Evangelista is proficient in programming languages (R, Matlab, PHP) and skilled in machine learning and web application development. She uses tools like WEKA, KNIME, and TensorFlow, and has expertise in NGS technology and database management.

Publication Top Notes:

• Transcriptator: An Automated Computational Pipeline to Annotate Assembled Reads and Identify Non-Coding RNA

  • Year: 2015

  • Citations: 15

• AnaLysis of Expression on Human Chromosome 21, ALE-HSA21: A Pilot Integrated Web Resource

  • Year: 2014

  • Citations: 15

• CDMS (Clinical Data Mining Software): A Cytokinome Data Mining System for Predictive Medicine of Chronic Inflammatory Diseases

  • Year: 2010

  • Citations: 7

• A Web-Oriented Software for the Optimization of Pooled Experiments in NGS for Detection of Rare Mutations

  • Year: 2016

  • Citations: 3

• Transcriptator: Computational Pipeline to Annotate Transcripts and Assembled Reads from RNA-Seq Data

  • Year: 2015

  • Citations: 3

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