The state of the art of protein-protein interaction networks: The role of the in "silico" approach

Organiser:

Rita Casadio, Dept.of Biology University of Bologna, Italy
e-mail: casadio@alma.unibo.it;
web: www.biocomp.unibo.it

more information: http://www.biocomp.unibo.it/school/html2004/

Background:

The biological datasets of physical and functional interactions within proteins in a living cell are rapidly expanding and the amount of data for visualisation and evaluation is daunting. This is specifically due to high throughput proteomics technologies that produce large volumes of protein-protein interaction data organised in networks.

It is presently believed that the complex functions of living cell are carried out through the concerted activity of many genes and gene products. Also this activity may be coordinated by the organisation of the genome into regulatory modules or sets of co-regulated genes that share a common function.

For an increasing number of organisms we can list the genes and the encoded proteins. While it is evident that the proteins execute the genetic programme, it is their expression profiles that can be detected under different conditions and ultimately tell us how the blue print of the cell drives the cellular machinery. We should therefore focus on the dynamics of the proteome and delineate all the interactions among the expressed proteins during cell development and in response to external stimuli.

The scale is rapidly changing: from individual protein interactions approached with genetic, biochemical and biophysical techniques to large scale methods that allow the detection of tens of thousands of genes simultaneously. The strategy therefore shifts from the 'one gene-one hypothesis' approach to more global strategies that analyse genes and proteins on a genome- and proteome-wide scale.

In the last years high throughput interaction- detection approaches have been introduced that can globally tackle the problem: the yeast two-hybrid system, protein complex purification techniques using mass spectrometry, correlated messenger RNA expression profiles and genetic interaction data. Also computational methods have been developed for interaction predictions derived from gene context analysis.
However several issues are still open. First of all, how reliable are the experimental data and how they can be benchmarked against a trusted reference set. Also how to perform comparative assessment of large data sets of protein-protein interactions and how to interpret it.

The problem of data analysis and their representation is a matter of debate, as well as the problem of function prediction from protein-protein interaction networks. Is it feasible to integrate large scale data sets with individual data of protein-protein interaction, including structural data?
Do we have interaction networks with enough internal structure to detect/predict "functional modules"?
With this scenario at hand, the Bologna School will focus on the present state of art of protein- protein interaction studies, from data analysis to their integration and assessment.

The main topics that will be explained and debated are:

• Global approaches to protein-protein interactions
• Protein complexes and proteome organisation in different organisms
• Reliability of experimental protein-protein interaction data
• Modular organisation of cellular networks
• Computational methods for the prediction of protein interactions
• Prediction of protein-protein interactions
• Complexity management in visualising protein interaction networks
• Correlation of protein-DNA and protein-protein interaction networks
  
  The training course will provide a unique forum both for experts and young researchers to meet and fruitfully debate the most recent achievements in the field.
• Furthermore a specific goal of this training course is to open a discussion on the methods that are presently available for the prediction of protein-protein interactions, their accuracy and limits with the purpose of stirring new ideas and prompting new developments, both theoretically and practically. This will highlight the role of predictive methods in structural genomics and particularly on computational proteomics, with benefits for the all-scientific community involved in studies of functional genomics and proteomics.

Venue:

The location of the training course will be in the oldest University in Europe (dating back to1088 A.C.), the University of Bologna. The course will be held in the biocomputing unit of the Interdepartmental Center for Biotechnological Researches (CIRB).

Dates:

Feburary 8th - 14th, 2004

List of speakers and Programme:

This is available on the training course web site.

Attendance:

Participants should have a ground level knowledge of computational biology and work experimentally and/or theoretically in the field of structural and functional genomics. Participants will be limited to a maximum number of 40.

Registration: closed