Computational and Quantitative Biology PhD

 Below the list of proposed projects for the XLI CQB PhD cycle. 

 

• Novel methods and tools for integrating large single-cell datasets using machine learning and artificial intelligence approaches (Abstract)

          PI: Prof. Claudia Angelini 

 

•  Integrated Omics Graph Medicine (Abstract)

PI: Prof. Davide Cacchiarelli

 

• Decoding Pediatric Neuroblastoma Through Multi-Omic and Single-Cell Bioinformatics (Abstract)
  
  PI: Prof. Capasso

 

• Integrative Machine Learning Framework for Accurate Prediction of Peptide Immunogenicity (Abstract)

  PI: Prof. Michele Ceccarelli

 

• Mechanisms of 3D chromatin re-structuring in healthy and pathogenic genomes (Abstract)

  PI: Prof. Andrea Maria Chiariello

 

• Web based platform for Structure and Functional -omics and Bioinformatics (Abstract)

  PI: Prof. Maria Luisa Chiusano

 

•  Polyphenol oxidases in wheat: expression atlas construction and allelic variant discovery under drought stress and microbial interactions (Abstract)

   PI: Prof. Nunzio D'Agostino, Dept. of Agricultural Sciences

 

• Biological catalysts for H₂ generation: challenges and opportunities of machine learning (Abstract)

         PI: Prof. De Simone , Prof. Lombardi

 

• Engineering Synthetic Gene Circuits for Gene Therapy (Abstract)

  PI: Prof. Diego di Bernardo

 

• Integrating Artificial Intelligence and Molecular Modeling: A Synergistic Approach to Nuclear Receptor Modulators Design (Abstract)

  PI: Prof. Lavecchia, Prof. Silipo, Prof. De Simone. 

 

• Lamina-Mediated Regulation of the DNA Damage Response and Chromatin Architecture at Site-Specific Double-Strand Breaks (Abstract)

  PI: Prof. Barbara Majello  

 

• Transfer learning methodologies for large-scale metagenomic analysis of the human microbiome (Abstract)

  PI: Prof. Edoardo Pasolli

 

• Integrative bioinformatics for Trans-omics networks representation and image analysis (Abstract)

         PI: Prof. Antonio M. Rinaldi (DIETI-UNINA), Dr. Giuseppe Coppola (ISASI-CNR)

 

• Exploiting multiomics data in human disesese model alignment (Abstract)

  PI: Prof. Giovanni Scala

 

• PI: Prof. Enza Torino (Abstract)

 

• Multi-Omics Meet Art and Archaeology (Abstract)

   PI:  Prof. Alessandro Vergara