Team Members

Enrico Capobianco

My group collaborators are:

INTERACTOMICS

Elisabetta Marras
Postdoc, PhD Statistics, Un of Rome (IT) - 2007

PROTEOMICS

Osvaldo Marullo
Master Thesis (in Italian, with appendix) in Bioinformatics applied to Personalized Medicine, Polaris Tech Park of Sardinia - Pula, 2007

The main themes that will be investigated:

1. generation and application of quantitative techniques for the study of complex biological systems and the analysis of multiomic data-driven problems

2. implementation of method fusion and data integration for both predictive modelling accuracy and dataset coverage

3. inference on biological systems and networks in order to reconstruct and approximate structural and dynamic features from observations and measurements

Methodological instruments:

• Statistical Inference & Predictive Modelling
• Data Mining & Analysis
  
• Regularization & Calibration
• Machine Learning & Signal Processing
• Reverse Engineering for Network Reconstruction
• High Dimensionality, Denoising, .....

Project Domain 1: (post-)Genomics and Statistical Bioinformatics

Currently investigated microarray data (please see state-of-the-art notes) with the aim of performing dimensionality reduction, denoising, profiling, feature selection, regression and classification.

Research areas of interest:

• Gene Regulation (data analysis, network dynamics modelling, regularized inference, control)
  
• miRNA and siRNA (non-coding RNA or ncRNA, RNA interference or RNAi, and related topics).
  
• Cancer-related studies (gene selection): ongoing joint work with Lucilla Ohno-Machado (Harvard Medical School,  Brigham and Women's Hospital) on cancer biomarkers (discovery, validation), and collaboration with Maria de Iorio, Division of Epidemiology, Public Health and Primary Care, Imperial College, London - UK.
  

• Neuroscience-related WGS studies (ongoing projects in collaboration with Pierandrea Muglia,  GlaxoSmithKline, Verona (IT).
  

Project Domain 2:  Interactomics 

Challenging problem areas:

• data integration from heterogeneous, incomplete and inaccurate biological information sources  and DBs
  
• analysis of gene- regulatory and PPI networks
  
• network inference and predictive modelling
  
• learning strongly/weakly predictive datasets
• method fusion and model selection

Through this link you can explore interactome-related information sources.

One main goal is to design gold standard reference datasets - best trusted representation of available physical and functional associations or interactions.

They can be used:

1. to assess the performance in terms of prediction power of ad hoc methods
   
2. to compare different algorithmic approaches designed to approximate a given reference
   
3. to check the quality and accuracy of any dataset

Existing PPIN can be sampled, decomposed, approximated, reconstructed, predicted: these are all objectives of our work.

The approach of interest in applications is:

• testing model organisms (known, well covered, eg Yeast)
• inferring on target organisms  (complex, lacking coverage and accuracy, eg Homo Sapiens)

A collaboration has started with the interactomics group (Gautam Chaurasia, Matthias E. Futschik) at Humboldt University Berlin, Theoretical Biology Dept.

Project Domain 3: Metabolomics

I am involved in core research activities under the newly EU/FP6 Marie Curie sponsored program named
Advanced Signal Processing for Ultra-Fast Magnetic Resonance Spectroscopy Imaging, and Training.

Research is carried out within an international consortium of institutes coordinated by Danielle Graveron-Demilly, UCBL, Lyon.

Theme: MRS - magnetic resonance spectroscopy.
Focus: signal and image processing, quantitative models and computational methods.

Project Domain 4: Proteomics

• 2D-Gel electrophoresis: in collaboration with P.R. Tome of CRS4 Bioinformatics Lab and Proteotech, algorithms and methods for image analysis and pattern recognition.
• Cancer biomarkers: discovery/validation aspects, data analysisi & mining, model calibration.
• Quantitative analysis in AFM-driven single protein studies (in collaboration with M. Vassalli and F. Sbrana @ CNR, CSDC and Dept of Physics, Un of Florence, IT) 

Project Domain 5: Multiscale Dynamics Models

QSB is involved in ongoing developments on Systems Biology Multiscale Dynamics Modelling.
Workshops have been attended at IMA, Minneapolis (USA) and posters have been presented.
Emphasis is on network multiscale decomposition via wavelets,  and on study of entropy, fractality, densification, etc.