Bioinformatics and computational biology are interdisciplinary areas of research that, exploiting scientific and technological advances in the field of information and communication technologies and bio-technologies, dealing with the study and interpretation of biological phenomena.
In particular, Bioinformatics deals with data analysis and interpretation of heterogeneous biological data, from a computational point of view. On the other hand, Computational Biology focuses on the design and development of computational models to represent and simulate biological systems, thus allowing the solution of related problems.
In recent years, these disciplines have aroused more and more interest in the medical field, and in particular in the field of the precision medicine, as they can provide suitable solutions at the level of the single patient (targeted therapies), thanks to the management, integration, elaboration and interpretation of the clinical and multi-omic data (e.g. genomics, transcriptomics, metabolomics, radiomics) provided.
Our research activity, therefore, is mainly focused on interpretation, integration and analysis of biological data and definition of innovative computational models, obtained using the most recent methodologies and techniques of Artificial Intelligence, based on machine learning algorithms, deep learning, statistical correlation analysis and predictive models, and bioinformatics tools.
These models aim at providing a solution for some open problems such as the integration of omics and clinical data, the representation and extraction of the features, the identification of the most appropriate learning techniques (supervised, unsupervised, semi-supervised, transfer learning) and their optimization for high-performance computing.
The prototypes of the developed models are first released as web services, to facilitate their dissemination and use among the international scientific community. The activity of the research group focuses on the application field of precision medicine due to the presence of in-house expertise in the biological domain. The research activity aims to obtain new knowledge in the clinical field through the integration and multivariate analysis of heterogeneous omics data.
The research group aims to develop diagnostic and prognostic measures for personalizing therapeutic treatments and the detection of non-invasive molecular biomarkers. To this end, we lead our research to define innovative computational models for the analysis and integration of multi-omic and clinical data, that can produce new knowledge in the clinical field. Given the properties of the data involved (Big Data), we optimise the proposed models through specific paradigms optimised for high-performance computing architectures.
In particular, the main objectives of the research activity are:
- the identification of molecular biomarkers (DNA, coding and non-coding RNA) in cancer and degenerative diseases (biomarker discovery, bulk/single-cell analysis);
- the characterisation of pathological states, through the study of gene expression data in healthy and tumour tissues(clinical and multi-omics analysis);
- design and/or identification of new generation therapeutic agents, through regulative network analysis (ncRNA therapeutics);
- the identification of gene mutations and isoforms related to pathological states, through the study of omic data (RNA-seq analysis from raw data).
- RARE.PLAT.NET – Diagnostic and therapeutic innovations for neuroendocrine and endocrine tumors and for glioblastoma through an integrated technological platform of clinical, genomic, ICT, pharmacological and pharmaceutical skills
- Development of an integrated radiomic and phenotypic system for the diagnosis, prognosis and personalized therapy of head and neck cancer therapy. Technological platform: eMORFORAD-Campania