BITS Meetings' Virtual Library:
Abstracts from Italian Bioinformatics Meetings from 1999 to 2013


766 abstracts overall from 11 distinct proceedings





Display Abstracts | Brief :: Order by Meeting | First Author Name
1. Bernaschi M, Castiglione F, Ferranti A, Gavrila C, Cesareni G
Dynamic simulation of protein interaction networks
Meeting: BITS 2006 - Year: 2006
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Topic: Computational systems biology

Abstract: Missing

2. Ceol A, Montecchi-Palazzi L, Persico M, Gavrila C, Castagnoli L, Cesareni G
The (new) MINT Database.
Meeting: BITS 2004 - Year: 2004
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Topic: Unspecified

Abstract: Scientists recognize that a complete description of cell physiology requires an understanding of the “global” protein interaction network. Thus, a database that collects this information, which is presently dispersed in the scientific literature (or accumulated by high throughput experiments), is an essential post genomic tool. MINT was conceived a couple of years ago, as a collaborative effort between the group of Molecular Genetics and the students of the PhD program of Molecular and Cellular Biology of the University of Rome Tor Vergata, MINT is a relational database designed to store data on functional interactions between proteins, and aims at being exhaustive in the description of the interaction including information, whenever available, about kinetic and binding constants and about the domains participating in the interaction. Presently MINT focuses on experimentally verified interactions extracted from the scientific literature by curators, with special emphasis on mammalian organisms. The MINT protein interaction database offers to the scientific community, a unique bioinformatic tool to design and interpret their experiments.

3. Cesareni G, Ceol A, Gavrila C, Montecchi-Palazzi L, Persico M, Schneider MV
Comparative Interactomics
Meeting: BITS 2005 - Year: 2005
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Topic: Database annotation and data mining

Abstract: Motivation:Similar to what has been achieved by comparing genome structures and protein sequences, we hope to obtain valuable information about systems evolution by comparing the organization of interaction networks stored in protein interaction databases and by analyzing their variation and conservation. Equally significantly we can learn whether and how to extend the network information obtained experimentally in well-characterized model systems to different organisms.



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