Detecting and characterizing the modular structure of the yeast transcription network

Cristino, Alexandre S., Andrade, Roberto F. S. and Costa, Luciano da F. (2009). Detecting and characterizing the modular structure of the yeast transcription network. In: Santo Fortunato, Giuseppe Mangioni, Ronaldo Menezes and Vincenzo Nicosia, Complex networks: Results of the 2009 International Workshop on Complex Networks (CompleNet 2009). International Workshop on Complex Networks (CompleNet 2009), Catania, Italy, (35-46). 26-27 May 2009. doi:10.1007/978-3-642-01206-8_4


Author Cristino, Alexandre S.
Andrade, Roberto F. S.
Costa, Luciano da F.
Title of paper Detecting and characterizing the modular structure of the yeast transcription network
Conference name International Workshop on Complex Networks (CompleNet 2009)
Conference location Catania, Italy
Conference dates 26-27 May 2009
Proceedings title Complex networks: Results of the 2009 International Workshop on Complex Networks (CompleNet 2009)   Check publisher's open access policy
Journal name Studies in Computational Intelligence   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2009
Sub-type Fully published paper
DOI 10.1007/978-3-642-01206-8_4
ISBN 9783642012051
9783642012068
ISSN 1860-949X
1860-9503
Editor Santo Fortunato
Giuseppe Mangioni
Ronaldo Menezes
Vincenzo Nicosia
Volume 207
Start page 35
End page 46
Total pages 12
Language eng
Abstract/Summary Systems biology and complex networks research will turn biology into a more precise and synthetic discipline. To date, complex network concepts have been used to study all diversity of networks, such as social organization to molecular interaction. In this study we are particularly interested in addressing some aspects of the structural and functional organization of biological networks. The construction of a comprehensive regulatory map of molecular systems will contribute to a better understanding of the ‘design principles’ of the genetic regulatory networks. We proposed a reliable strategy in blending bioinformatics and complex network research for characterization of modular structure in sparse biological networks with low average node degree, as for the yeast transcription network (YTN).We find that the YTN is highly modular and those modules have specific functions. In addition, communities or modules sharing structural properties are also sharing some functional traits, which is a remarkable finding. Our approach could be used for helping biologists to address specific biological questions by designing hypothesis-driven experiments.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Conference Paper
Collection: Queensland Brain Institute Publications
 
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