DST UniSannio
Bioinformatics Lab
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About

The Bioinformatics Lab at University of Sannio is led by Luigi Cerulo and Francesco Napolitano, focusing on Systems Biology, AI-driven omics data analysis, and Computational Drug Discovery.



Systems Biology

Exploring biological data to uncover complex molecular mechanisms

AI-driven omics data analysis

Leveraging Artificial Intelligence to make biological predictions from omics data.

Computational Drug Discovery

Indentifying small molecules for clinical and laboratory applications.



Bioinformatics research activities at the University of Sannio were initiated in 2000 by Michele Ceccarelli and focused on the study of informatic processes in biological systems. As biological data began to grow exponentially, the lab focused toward data science approaches in bioinformatics under the co-direction of Luigi Cerulo from 2009. Starting in 2021, the Bioinformatics Lab has been led by Luigi Cerulo and Francesco Napolitano and employs advanced techniques to explore biological data, predict molecular mechanisms, and identify novel drugs and therapeutic targets, driving innovation in bioinformatics research.

News and Publications


10 Sep 2024

"Multi-task deep latent spaces for cancer survival and drug sensitivity prediction", in Bioinformatics

09 Sep 2024

CIBB 2024 was great!

The 19th conference on Computational Intelligence methods for Bioinformatics and Biostatistics has just finished and was a great success! Find more info (and pictures) at http://cibb2024.unisannio.it!

29 Jul 2024

"Altered centriolar cohesion by CEP250 and appendages impact outcome of patients with pancreatic cancer", in Pancreatology

01 May 2024

"AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data", in Briefings in Bioinformatics

15 Mar 2024

"Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions expression data", in Journal of Translational Medicine

01 Feb 2024

We are hosting CIBB 2024!

We are organizing the 19th conference on Computational Intelligence methods for Bioinformatics and Biostatistics. Find more info at http://cibb2024.unisannio.it!

Tools


Gep2pep R/Bioconductor package

Pathway Expression Profiles (PEPs) are based on the expression of pathways (defined as sets of genes) as opposed to individual genes. This package converts gene expression profiles to PEPs and performs enrichment analysis of both pathways and experimental conditions, such as “drug set enrichment analysis” and “gene2drug” drug discovery analysis respectively.

ggmol R package

An R package designed for creating publication ready visualizations based on small molecules within the ggplot2 framework. The packages is built over ChemmineR and allows to simplify visualization by only relying on the molecules SMILES strings.

Repo R package

A data manager for the R environment meant to abstract file system operations. It builds one (or more) centralized repositories where R objects are stored together with rich annotations, including code chunks, allowing for easily searching and retrieving data.

Facilities


  • Informatics lab

    50 desktop computers equipped with LTS Ubuntu and major bioinformatics tools for laboratory activities.

  • Superdome Flex

    224 CPU cores Intel(R) Xeon(R) Platinum 8280 CPU @ 2.70GHz, 1.5 TB RAM, 150TB storage, 1 GPU NVIDIA Tesla V100.

  • Server cluster

    Cluster of 7 CPU servers and 1 GPU unit including a total of 400 CPU cores, 4 TB RAM, 600TB storage, 6 GPU NVIDIA. Hosted at Biogem - Molecular Biology and Genetics Research Institute in Ariano Irpino (AV).

People


Current members

Luigi Cerulo

Lab Director

Francesco Napolitano

Lab Director

Marco Nigro

Postdoctoral Fellow

Antonio Ammendola

PhD student

Luca Faretra

PhD Student

Diana Parente

Intern


Former members

Felicita Masone

Bachelor student

Donatella Pierri

Bachelor student

Francesco Saccomando Ciaramella

Intern, Bachelor student