Emilia Nunzi

Designation:
Doctor
Department:
Deparment of Medicine and Surgery
University:
University of Perugia
Country:
Italy
Email:
casareali@alice.it
Journal Associated: Journal of Biology and Medicine Biography:

I am a researcher at the Department of Medicine and Surgery at the University of Perugia. I obtained my PhD in Information Sciences and Technologies from the University of Perugia in 2001, with a dissertation focused on the application of statistics to experimental data on information devices and systems. My research evolved into estimation and detection theory, eventually shifting towards biological and medical sciences. In 2013, I joined the Genomic Center at the University of Perugia. Through participation in international research projects and collaborations, I have gained significant expertise in statistical methods and software tools designed for biomedical research. These solutions were implemented on both local and distributed computing platforms.

Over the past five years, I have intensively applied data science and machine learning techniques to massive biological datasets, extracting meaningful information through the integration of statistical and probabilistic visualizations. Recently, I have successfully applied these skills to genomic datasets, particularly in targeted sequencing (16S, ITS) and RNA-seq. My research focuses on developing effective techniques for genomic information extraction, emphasizing visualization methods tailored to specific applications. Additionally, I have applied both classical and advanced statistical techniques to enhance the precision of biomedical data parameter estimates, even for small-volume datasets such as those from seronegative elderly or neonatal infants.

I am currently a highly motivated and skilled bioinformatician with a robust background in genomics, specializing in the analysis of amplicon sequencing data and contributing to cutting-edge scientific advancements.

Research Interest: In the last ten years her research interests were on the metrological characterization of systems biology devices, remote control of instrumentation for biological data processing, and biostatistics analyses applied to biomedical data, with particular concern to In the last ten years, my research has focused on the metrological characterization of systems biology devices, remote control of instrumentation for biological data processing, and biostatistical analyses applied to biomedical data. This includes the immunogenicity evaluation of influenza vaccines and the diversity and differential analysis of microbiome sequencing data. Specifically, I have developed translational research methodologies in the biomedical field, processing data collected by biomedical devices and instruments. My skills include:

  • Developing reliable decision-making tools using statistical techniques applied to experimental data.
  • Implementing data science and machine learning techniques on big data to extract knowledge and visualize statistical and probabilistic results.
  • Designing algorithms and prototypes for highly reliable fault detection from measurement data acquired through medical instrumentation.
  • Creating algorithms for automatic imaging recognition systems, translating research findings into practical biomedical solutions.

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