Research Overview
Our research is directed towards the development of new computational models for the identification of disease-associated markers using functional genomic and systems biology approaches.
Relevant examples of our current research include:
Data management and integration of high-throughput datasets
Data management and integration of high-throughput datasets for the development of models for personalized medicine and the identification of therapeutic targets. Design of biological databases, bio-statistics and epidemiology.
Biomarker identification
Identification of biomarker candidates associated with sample stratification, disease susceptibility or clinical outcome.
Systems biology
Inference of gene and protein networks in complex biological systems of biomedical interest. Design and implementation of mathematical algorithms for the modelling of biological processes.
Past projects
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Connections between epigenetics and microRNAs during embryonic stem cell differentiation
This project aims at elucidating the interactions between the epigenetic modifications and microRNAs during human embrionic stem cell differentiation.
Wieslawa Mentzen, Paolo Uva -
Differential gene expression in mice over-expressing placenta growth factor (PLGF)
This project concerns the analysis of gene expression data from mice over-expressing placenta growth factor (PLGF). The overall objective of this study is to identify genes and pathways which are affected by the over-expression of PLGF.
Fabio Maggio, Paolo Uva -
Genome-wide identification of in-vivo FOXL2–DNA binding sites from ChIP-Seq data
This project concerns the analysis of ChIP-Seq data for the identification of putative FOXL2 binding site in mouse ovary and hypophysis.
Andrea Sbardellati -
Identification of the mechanism of action of Toll-like receptor (TLR) 7 and TLR9 antagonist
This project aims at evaluating the mechanism of action of a Toll-like receptor (TLR) 7 and TLR9 antagonist candidates in a model of hyperlipidemia.
Wieslawa Mentzen, Paolo Uva -
Integrated analysis of mRNAs and microRNAs during B cell to plasma cell differentiation
The main goal of this study is the identification of the transcriptional changes of mRNAs and microRNAs and their interactions during the B cell to plasma cell differentiation.
Wieslawa Menzen, Paolo Uva -
MiRWare: MicroRNA Cancer Warehouse
MicroRNAs represent a challenging research areas in cancer genomics since they regulate many distinct mRNA targets and are involved in key biological processes.
Massimiliano Orsini, Enrico Capobianco
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Development of a prognostic biomarker in diffuse large B-cell lymphoma (DLBCL)
This project concerns the analysis of gene expression data from diffuse large B-cell lymphoma. The overall objective of this study is the identification of a biomarker able to predict the response to treatment and survival.
Fabio Maggio, Andrea Sbardellati -
Genetically modified skin equivalents: differential gene expression and pathway analysis
This project concerns the analysis of gene expression data from genetically modified skin equivalents. The overall objective of this study is to uncover the effect of the NGF transgene on the keratinocyte pathways.
Fabio Maggio, Paolo Uva -
In silico biomarker discovery in the realm of transcriptomics and proteomics
Based on our previous joint project involving the group of L. Ohno-Machado at Harvard University, and named Atlantic, a large-scale manual re-annotation of data samples from Gene Expression Omnibus (GEO) and ArrayExpress (AE) was simultaneously performed with the aim to validate in silico a list of candidate cancer biomarkers using the available public data.
Massimiliano Orsini, Antonella Travaglione, Elisabetta Marras, Enrico Capobianco
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Computational Prediction of Drug Cardiac Toxicity
This project aims to model, simulate, and ultimately predict the impact of pharmacological compounds on the heart's rhythm using computer models.
Gianmauro Cuccuru, Giorgio Fotia, Fabio Maggio -
Differential network analysis of genetically modified skin equivalents
The goal of this project is to infer the gene networks related to an "untreated" and a "treated" epidermic tissue in order to identify the most important differences between their pathways.
Alberto de la Fuente, Andrea Pinna, Nicola Soranzo, Massimiliano Orsini, Giorgio Fotia, Fabio Maggio -
Disease Differential Networking
The ultimate goal of application of Systems Biology to disease research is to elucidate the specific regulatory networks that have been impaired in a disease state.
Alberto de la Fuente, Nicola Soranzo, Andrea Pinna -
High performance computational biology by means of GPU-based hardware systems
The advent of general purpose hardware accelerators like GPUs (Graphics Processing Units) has moved one step forward the state-of-the-art of computer science.
Scientific analyses that in the recent past did require a brute-force approach based on supercomputing facilities, can now in principle run at the researcher desk, thanks to the introduction of new chips with peak performance around 1 TFlop/s. This requires hybrid hardware models, where many GPUs and CPUs work together to perform general purpose computing tasks as well as new advances in software tools and numerical algorithms.Gianmauro Cuccuru, Giorgio Fotia, Fabio Maggio -
Interactomics Inference
Bio-interactomes (especially human) inference methods and integrative applications (especially cancer).
Elisabetta Marras, Antonella Travaglione, Massimiliano Orsini, Enrico Capobianco -
SysGenSIM: A Systems Genetics Simulator for Evaluations of Analysis Methods
New algorithms for genomic data analysis and gene network inference are proposed at a high rate, but it is unknown how reliable the inferred models are. Therefore we need benchmarks for unbiased evaluation of the proposed methods. To this aim we have developed SysGenSIM for simulating appropriately complex datasets for the evaluation of Systems Genetics (SG) data analysis.
Alberto de la Fuente, Andrea Pinna, Nicola Soranzo
