The Molecular INTeraction database (MINT, ) aims at storing, in a structured format, information about molecular interactions (MIs) by extracting experimental details from work published in peer-reviewed journals. At present the MINT team focuses the curation work on physical interactions between proteins. Genetic or computationally inferred interactions are not included in the database. Over the past four years MINT has undergone extensive revision. The new version of MINT is based on a completely remodeled database structure, which offers more efficient data exploration and analysis, and is characterized by entries with a richer annotation. Over the past few years the number of curated physical interactions has soared to over 95 000. The whole dataset can be freely accessed online in both interactive and batch modes through web-based interfaces and an FTP server. MINT now includes, as an integrated addition, HomoMINT, a database of interactions between human proteins inferred from experiments with ortholog proteins in model organisms ().
The behavior, morphology and response to stimuli in biological systems are dictated by the interactions between their components. These interactions, as we observe them now, are therefore shaped by genetic variations and selective pressure. Similar to what has been achieved by comparing genome structures and protein sequences, we hope to obtain valuable information about systemsÕ evolution by comparing the organization of interaction networks 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. We conclude from our analysis that, despite the recent completion of several high throughput experiments aimed at the description of complete interactomes, the available interaction information is not yet of sufficient coverage and quality to draw any biologically meaningful conclusion from the comparison of different interactomes. Thus, the transfer of network information obtained from simple organism to evolutionary distant species should be carried out and considered with caution. By using smaller higher-confidence datasets, a larger fraction of interactions is shown to be conserved; this suggests that with the development of more accurate experimental and informatic approaches, we will soon be in the position to study the network evolution.
Proteomics data can be diverse and complex, and are typically produced on a large scale. To allow sharing and centralized storage and dissemination of such results, the Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has created a set of community standards for the exchange of mass spectrometry and protein interaction data. We describe the origins and overall concepts behind these standards, as well as the individual efforts that are ongoing in the field of mass spectrometry proteomics and protein interactions.
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