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 systems' 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. © 2005 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Cesareni, G., Ceol, A., Gavrila, C., Palazzi, L., Persico, M., Schneider, M. (2005). Comparative interactomics. FEBS LETTERS, 579(8), 1828-1833 [10.1016/j.febslet.2005.01.064].

Comparative interactomics

CESARENI, GIOVANNI;
2005-01-01

Abstract

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 systems' 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. © 2005 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
2005
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore BIO/18 - GENETICA
English
Con Impact Factor ISI
Evolution; High-throughput experiment; Networks; Protein interaction
Cesareni, G., Ceol, A., Gavrila, C., Palazzi, L., Persico, M., Schneider, M. (2005). Comparative interactomics. FEBS LETTERS, 579(8), 1828-1833 [10.1016/j.febslet.2005.01.064].
Cesareni, G; Ceol, A; Gavrila, C; Palazzi, L; Persico, M; Schneider, M
Articolo su rivista
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/37550
Citazioni
  • ???jsp.display-item.citation.pmc??? 13
  • Scopus 51
  • ???jsp.display-item.citation.isi??? 39
social impact